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| power bi nlp: Deep Natural Language Processing and AI Applications for Industry 5.0 Tanwar, Poonam, Saxena, Arti, Priya, C., 2021-06-25 To sustain and stay at the top of the market and give absolute comfort to the consumers, industries are using different strategies and technologies. Natural language processing (NLP) is a technology widely penetrating the market, irrespective of the industry and domains. It is extensively applied in businesses today, and it is the buzzword in every engineer’s life. NLP can be implemented in all those areas where artificial intelligence is applicable either by simplifying the communication process or by refining and analyzing information. Neural machine translation has improved the imitation of professional translations over the years. When applied in neural machine translation, NLP helps educate neural machine networks. This can be used by industries to translate low-impact content including emails, regulatory texts, etc. Such machine translation tools speed up communication with partners while enriching other business interactions. Deep Natural Language Processing and AI Applications for Industry 5.0 provides innovative research on the latest findings, ideas, and applications in fields of interest that fall under the scope of NLP including computational linguistics, deep NLP, web analysis, sentiments analysis for business, and industry perspective. This book covers a wide range of topics such as deep learning, deepfakes, text mining, blockchain technology, and more, making it a crucial text for anyone interested in NLP and artificial intelligence, including academicians, researchers, professionals, industry experts, business analysts, data scientists, data analysts, healthcare system designers, intelligent system designers, practitioners, and students. |
| power bi nlp: Mastering Power BI Chandraish Sinha, 2024-05-28 Take a deep dive into the dynamic world of Power BI! KEY FEATURES ● In-depth knowledge of Power BI, demonstrated through step-by-step exercises. ● Covers data modeling, visualization, and implementing security with complete hands-on training. ● Includes a project that simulates a realistic business environment from start to finish. ● This version teaches about Artificial Intelligence visuals in Power BI. DESCRIPTION Mastering Power BI covers the entire Power BI implementation process. The readers will be able to understand all the concepts covered in this book, from data modeling to creating powerful visualizations. This book begins with concepts and terminology such as the star-schema, dimensions, and facts. It explains multi-table dataset and demonstrates how to load these tables into Power BI. It shows how to load stored data in various formats and create relationships. Readers will also learn more about Data Analysis Expressions (DAX). This book is a must for developers to learn how to extend the usability of Power BI, to explore meaningful and hidden data insights. Throughout the book, you keep on learning about the concepts, techniques, and expert practices on loading and shaping data, visualization design, and security implementation. The second edition of Mastering Power BI book adheres to the first edition in terms of providing the basics of business intelligence and Power BI; however, it introduces new concepts and features in terms of data transformation, data profiling, custom hierarchies, AI visuals, and many more. WHAT YOU WILL LEARN ● Learn about Business Intelligence (BI) concepts and their contribution in business analytics. ● Learn to connect, load, and transform data from disparate data sources. ● Create and execute powerful DAX calculations. ● Design various visualizations to prepare insightful reports and dashboards. WHO THIS BOOK IS FOR This book is for anyone interested in learning how to use Power BI desktop or starting a career in business intelligence and analytics. While it covers all the fundamentals, it is recommended that the reader be familiar with MS Excel and database concepts. TABLE OF CONTENTS 1. Understanding the Basics 2. Connect and Shape 3. Advanced Data Transformations 4. Optimize Your Data Model 5. Data Analysis Expressions 6. Visualizations in Power BI 7. Drill Through and Drill Down Reports 8. Artificial Intelligence in Power BI 9. Power BI Service 10. Securing Your Application |
| power bi nlp: Ultimate Apache Superset for Data Visualization and Analytics: Leverage Apache Superset to Create Interactive Dashboards and Master Modern Business Intelligence Bragadeesh Sundararajan, 2025-04-07 Apache Superset to Master Data Visualization and Build High-Impact BI Solutions Key Features● Learn to install, configure, and use Superset to create visualizations and build interactive dashboards.● Apply your learning to real-world data scenarios and business use cases, ensuring you can immediately apply these skills in your role.● Customize Superset with custom visualizations, integrate it with modern data pipelines, and learn how to deploy it in production environments. Book DescriptionApache Superset is a powerful open-source data visualization and business intelligence platform that enables professionals to create interactive dashboards effortlessly. With its user-friendly interface and broad compatibility with various data sources, Superset helps users uncover insights and make informed, data-driven decisions in real time. Ultimate Apache Superset for Data Visualization and Analytics offers a structured, hands-on approach to mastering Apache Superset. It begins with installation and configuration, guiding you through building your first visualization and dashboard. As you progress, you’ll explore advanced features such as SQL Lab, custom visualizations, and security management. The book also covers optimizing dashboards, integrating Superset with data pipelines, and deploying it in production environments. Each chapter includes practical examples, best practices, and real-world use cases to reinforce learning. By the end, you’ll have the expertise to build high-impact, interactive dashboards and confidently deploy Apache Superset in production. Whether you're a data analyst, engineer, or business professional, this book equips you with the skills to scale and customize Superset for your organization’s needs. Don't get left behind—unlock the full potential of Apache Superset and take your data visualization to the next level! What you will learn● Set up and configure Apache Superset for data visualization and BI● Design interactive dashboards and compelling data visualizations effortlessly● Use SQL Lab to query and explore datasets with precision● Develop custom visualizations and extend Superset with plugins● Implement role-based access control (RBAC) for secure data governance● Deploy, scale, and optimize Superset for enterprise-ready BI solutions |
| power bi nlp: UX for AI Greg Nudelman, 2025-04-30 Learn to research, plan, design, and test the UX of AI-powered products Unlock the future of design with UX for AI—your indispensable guide to not only surviving but thriving in a world powered by artificial intelligence. Whether you're a seasoned UX designer or a budding design student, this book offers a lifeline for navigating the new normal, ensuring you stay relevant, valuable, and indispensable to your organization. In UX for AI: A Framework for Designing AI-Driven Products, Greg Nudelman—a seasoned UX designer and AI strategist—delivers a battle-tested framework that helps you keep your edge, thrive in your design job, and seize the opportunities AI brings to the table. Drawing on insights from 35 real-world AI projects and acknowledging the hard truth that 85% of AI initiatives fail, this book equips you with the practical skills you need to reverse those odds. You'll gain powerful tools to research, plan, design, and test user experiences that seamlessly integrate human-AI interactions. From practical design techniques to proven user research methods, this is the essential guide for anyone determined to create AI products that not only succeed but set new standards of value and impact. Inside the book: Hands-on exercises: Build your confidence and skills with practice UX design tasks like Digital Twin and Value Matrix, which you can immediately apply to your own AI projects. Common AI patterns and best practices: Explore design strategies for LLMs (Large Language Models), search engines, copilots, and more. Proven user research strategies: Learn how to uncover user needs and behaviors in this brave new world of AI-powered design. Real-world case studies: See how simple, practical UX approaches have prevented multimillion-dollar failures and unlocked unprecedented value. Perfect for any UX designer working with AI-enabled and AI-driven products, UX for AI is also a must-read resource for designers-in-training and design students with an interest in artificial intelligence and contemporary design. |
| power bi nlp: Embracing the Cloud as a Business Essential Rai, Pankaj Kumar, Ahmad, Tanveer, Pandey, B.K., 2025-04-08 Through cloud computing, a vast amount of processing power may now be accessed with only a few clicks of the mouse. As a consequence of this, the manner in which businesses approach computers for the purposes of conducting research and carrying out commercial activities will undergo a considerable transition. This move marks a substantial democratization of computing power, which means that it will have an influence on every industry and will ignite the flames of innovation at a rate that has never been seen before. Embracing the Cloud as a Business Essential explores the transformation brought about by the shift in the way that processing power is utilized. It discusses Computer as a Commodity rather than Computer as a Service as the proper moment for enterprises to begin addressing its utilization. Covering topics such as cost management, marginalized communities, and smart contracts, this book is an excellent resource for business leaders, computer programmers, cloud developers, professionals, researchers, scholars, academicians, and more. |
| power bi nlp: Hands-On Python Natural Language Processing Aman Kedia, Mayank Rasu, 2020-06-26 This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples |
| power bi nlp: Data Visualization Tools for Business Applications Muniasamy, M. Anandhavalli, Naim, Arshi, Kumar, Anuj, 2024-09-13 In today’s data-driven business landscape, the ability to extract insights and communicate complex information effectively is paramount. Data visualization has emerged as a powerful tool for businesses to make informed decisions, uncover patterns, and present findings in a compelling manner. From executives seeking strategic insights to analysts delving into operational data, the demand for intuitive and informative visualizations spans across all levels of an organization. Data Visualization Tools for Business Applications comprehensively equips professionals with the knowledge and skills necessary to leverage data visualization tools effectively. Through a blend of theory and hands-on case studies, this book explores a wide range of data visualization tools, techniques, and methodologies. Covering topics such as business analytics, cyber security, and financial reporting, this book is an essential resource for business executives and leaders, marketing professionals, data scientists, entrepreneurs, academicians, educators, students, decision-makers and stakeholders, and more. |
| power bi nlp: Cognitive Internet of Things Pethuru Raj, Anupama C. Raman, Harihara Subramanian, 2022-03-29 The Internet of Things (IoT) concept is defined as a flexible and futuristic network where all the different types of devices and smart objects can become seamlessly connected to each other and can actively participate in all types of processes which are happening around us. The grand objective of making physical, mechanical, electrical, and electronic devices to use the deeper and extreme connectivity and service-enablement techniques is to make them intelligent in their deeds, decisions, and deals. Cognitive IoT is the application of cognitive computing technologies to the data which is generated by the connected devices of the IoT ecosystem. Cognition means thinking; however, computers are not yet fully capable of mimicking human like thought. However, the present-day computer systems can perform some functions which are like the capability of human beings to think. Cognitive Internet of Things: Enabling Technologies, Platforms, and Use Cases explains the concepts surrounding Cognitive IoT. It also looks at the use cases and such supporting technologies as artificial intelligence and machine learning that act as key enablers of Cognitive IoT ecosystem. Different Cognitive IoT enabled platforms like IBM Watson and other product specific use cases like Amazon Alexa are covered in depth. Other highlights of the book include: Demystifying the cognitive computing paradigm Delineating the key capabilities of cognitive cloud environments Deep learning algorithms for cognitive IoT solutions Natural language processing (NLP) methods for cognitive IoT systems Designing a secure infrastructure for cognitive IoT platforms and applications |
| power bi nlp: AI-Powered Business Intelligence Tobias Zwingmann, 2022-06-10 Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision making. With this practical book featuring hands-on examples in Power BI with basic Python and R code, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, document, and image files. Author Tobias Zwingmann helps BI professionals, business analysts, and data analytics understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists. Learn how AI can generate business impact in BI environments Use AutoML for automated classification and improved forecasting Implement recommendation services to support decision-making Draw insights from text data at scale with NLP services Extract information from documents and images with computer vision services Build interactive user frontends for AI-powered dashboard prototypes Implement an end-to-end case study for building an AI-powered customer analytics dashboard |
| power bi nlp: Intersection of AI and Business Intelligence in Data-Driven Decision-Making Natarajan, Arul Kumar, Galety, Mohammad Gouse, Iwendi, Celestine, Das, Deepthi, Shankar, Achyut, 2024-08-28 In today's rapidly evolving business landscape, organizations are inundated with vast amounts of data, making it increasingly challenging to extract meaningful insights and make informed decisions. The traditional business intelligence (BI) approach must often address the complexity and speed required for effective decision-making in this data-rich environment. As a result, many businesses need help to leverage their data to drive sustainable growth and remain competitive. Intersection of AI and Business Intelligence in Data-Driven Decision-Making presents a transformative solution to this pressing challenge. By exploring the convergence of artificial intelligence (AI) and BI, our book provides a comprehensive framework for leveraging AI-powered BI to revolutionize data analysis, predictive modeling, and decision-making processes. Readers will gain valuable insights into practical applications, emerging trends, and ethical considerations, inspiring and exciting them about the potential of AI in driving business success. |
| power bi nlp: The Future of Digital-Physical Interactions Siva Sathyanarayana Movva, Siva Karthik Devineni, Moses Michael Meitivyeki, Ankur Tak, Kodanda Rami Reddy Manukonda, 2024-06-06 TOPICS IN THE BOOK Development of Digital Twins for Urban Water Systems AI-Enhanced Data Visualization: Transforming Complex Data into Actionable Insights Global Positioning System Signal Verification through Correlation Function Distortion and Received Power Tracking Risk Management in Agile Al/Ml Projects: Identifying and Mitigating Data and Model Risks Addressing Challenges in Test Automation Adoption: A Study on Strategies for Overcoming Barriers to Seamless QA Integration |
| power bi nlp: AI as a Tool for Qualitative Analysis: Past and Present Petri Luosto, 2025-04-30 Can a machine help us understand the past? Can it shed light on the present? In this groundbreaking exploration, Petri Luosto engages in a rich dialogue with AI; specifically ChatGPT; to examine the power and limitations of artificial intelligence in historical and qualitative analysis. From the decisions of Tokugawa Ieyasu and Napoleon to the complexities of modern geopolitics, Luosto tests how AI interprets context, language, and human judgment. Combining deep historical insight with a clear-eyed look at cutting-edge technology, this book offers readers a rare blend of reflection, technical explanation, and philosophical inquiry. It invites historians, students, and curious minds to witness how AI can assist; not replace; our understanding of why people made the decisions they did. This is not just a book about AI. It is a book with AI; part guide, part experiment, and part conversation with the future. This summary was made by ChatGPT. |
| power bi nlp: Hands-On Natural Language Processing with Python Rajesh Arumugam, Rajalingappaa Shanmugamani, 2018-07-18 Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today’s NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehensive guide is also useful for deep learning users who want to extend their deep learning skills in building NLP applications. All you need is the basics of machine learning and Python to enjoy the book. |
| power bi nlp: Natural Language Processing and Computational Linguistics Bhargav Srinivasa-Desikan, 2018-06-29 Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. Key Features Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms Learn deep learning techniques for text analysis Book Description Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. What you will learn Why text analysis is important in our modern age Understand NLP terminology and get to know the Python tools and datasets Learn how to pre-process and clean textual data Convert textual data into vector space representations Using spaCy to process text Train your own NLP models for computational linguistics Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn Employ deep learning techniques for text analysis using Keras Who this book is for This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you! |
| power bi nlp: Natural Language Processing with TensorFlow Thushan Ganegedara, 2018-05-31 Write modern natural language processing applications using deep learning algorithms and TensorFlow Key Features Focuses on more efficient natural language processing using TensorFlow Covers NLP as a field in its own right to improve understanding for choosing TensorFlow tools and other deep learning approaches Provides choices for how to process and evaluate large unstructured text datasets Learn to apply the TensorFlow toolbox to specific tasks in the most interesting field in artificial intelligence Book Description Natural language processing (NLP) supplies the majority of data available to deep learning applications, while TensorFlow is the most important deep learning framework currently available. Natural Language Processing with TensorFlow brings TensorFlow and NLP together to give you invaluable tools to work with the immense volume of unstructured data in today’s data streams, and apply these tools to specific NLP tasks. Thushan Ganegedara starts by giving you a grounding in NLP and TensorFlow basics. You'll then learn how to use Word2vec, including advanced extensions, to create word embeddings that turn sequences of words into vectors accessible to deep learning algorithms. Chapters on classical deep learning algorithms, like convolutional neural networks (CNN) and recurrent neural networks (RNN), demonstrate important NLP tasks as sentence classification and language generation. You will learn how to apply high-performance RNN models, like long short-term memory (LSTM) cells, to NLP tasks. You will also explore neural machine translation and implement a neural machine translator. After reading this book, you will gain an understanding of NLP and you'll have the skills to apply TensorFlow in deep learning NLP applications, and how to perform specific NLP tasks. What you will learn Core concepts of NLP and various approaches to natural language processing How to solve NLP tasks by applying TensorFlow functions to create neural networks Strategies to process large amounts of data into word representations that can be used by deep learning applications Techniques for performing sentence classification and language generation using CNNs and RNNs About employing state-of-the art advanced RNNs, like long short-term memory, to solve complex text generation tasks How to write automatic translation programs and implement an actual neural machine translator from scratch The trends and innovations that are paving the future in NLP Who this book is for This book is for Python developers with a strong interest in deep learning, who want to learn how to leverage TensorFlow to simplify NLP tasks. Fundamental Python skills are assumed, as well as some knowledge of machine learning and undergraduate-level calculus and linear algebra. No previous natural language processing experience required, although some background in NLP or computational linguistics will be helpful. |
| power bi nlp: Transfer Learning for Natural Language Processing Paul Azunre, 2021-08-31 Build custom NLP models in record time by adapting pre-trained machine learning models to solve specialized problems. Summary In Transfer Learning for Natural Language Processing you will learn: Fine tuning pretrained models with new domain data Picking the right model to reduce resource usage Transfer learning for neural network architectures Generating text with generative pretrained transformers Cross-lingual transfer learning with BERT Foundations for exploring NLP academic literature Training deep learning NLP models from scratch is costly, time-consuming, and requires massive amounts of data. In Transfer Learning for Natural Language Processing, DARPA researcher Paul Azunre reveals cutting-edge transfer learning techniques that apply customizable pretrained models to your own NLP architectures. You’ll learn how to use transfer learning to deliver state-of-the-art results for language comprehension, even when working with limited label data. Best of all, you’ll save on training time and computational costs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build custom NLP models in record time, even with limited datasets! Transfer learning is a machine learning technique for adapting pretrained machine learning models to solve specialized problems. This powerful approach has revolutionized natural language processing, driving improvements in machine translation, business analytics, and natural language generation. About the book Transfer Learning for Natural Language Processing teaches you to create powerful NLP solutions quickly by building on existing pretrained models. This instantly useful book provides crystal-clear explanations of the concepts you need to grok transfer learning along with hands-on examples so you can practice your new skills immediately. As you go, you’ll apply state-of-the-art transfer learning methods to create a spam email classifier, a fact checker, and more real-world applications. What's inside Fine tuning pretrained models with new domain data Picking the right model to reduce resource use Transfer learning for neural network architectures Generating text with pretrained transformers About the reader For machine learning engineers and data scientists with some experience in NLP. About the author Paul Azunre holds a PhD in Computer Science from MIT and has served as a Principal Investigator on several DARPA research programs. Table of Contents PART 1 INTRODUCTION AND OVERVIEW 1 What is transfer learning? 2 Getting started with baselines: Data preprocessing 3 Getting started with baselines: Benchmarking and optimization PART 2 SHALLOW TRANSFER LEARNING AND DEEP TRANSFER LEARNING WITH RECURRENT NEURAL NETWORKS (RNNS) 4 Shallow transfer learning for NLP 5 Preprocessing data for recurrent neural network deep transfer learning experiments 6 Deep transfer learning for NLP with recurrent neural networks PART 3 DEEP TRANSFER LEARNING WITH TRANSFORMERS AND ADAPTATION STRATEGIES 7 Deep transfer learning for NLP with the transformer and GPT 8 Deep transfer learning for NLP with BERT and multilingual BERT 9 ULMFiT and knowledge distillation adaptation strategies 10 ALBERT, adapters, and multitask adaptation strategies 11 Conclusions |
| power bi nlp: Managing Enterprise Business Intelligence: A Comprehensive Guide 2025 Saurabhkumar Sumatprakash Gandhi, Prof (Dr) Moparthi Nageswara Rao, PREFACE In the rapidly evolving digital landscape, data has become one of the most valuable assets for organizations. With vast amounts of information being generated every second, businesses are under constant pressure to transform this data into actionable insights that drive decision-making, strategy, and innovation. Business Intelligence (BI) is at the forefront of this transformation, enabling organizations to harness the power of their data and convert it into meaningful, real-time insights. The role of BI within enterprises has grown significantly over the past few decades, evolving from simple reporting tools to complex, integrated platforms capable of advanced analytics, machine learning, and predictive modeling. However, as organizations continue to scale and their data ecosystems grow more complex, effectively managing enterprise BI systems has become a critical challenge. This book, Managing Enterprise Business Intelligence: A Comprehensive Guide, aims to provide readers with a thorough understanding of how to design, implement, and manage a successful enterprise BI strategy. It is designed for business leaders, IT professionals, data analysts, and BI managers who are seeking to navigate the challenges of managing BI systems at an enterprise level. Whether you are in the initial stages of adopting BI or looking to optimize an existing system, this book provides both the foundational knowledge and advanced strategies necessary for success. The first part of this book explores the fundamental concepts of Business Intelligence, including data integration, data governance, and the several types of BI tools and technologies available. It delves into how BI fits into the broader context of enterprise data management, and how to align BI strategies with organizational goals. With BI being a critical driver of organizational decision-making, it is crucial that businesses understand how to effectively leverage these tools to maximize value. As we move further into the book, we dive deep into the practicalities of managing an enterprise BI environment. We examine the organizational aspects of BI management, including the roles of BI teams, collaboration across departments, and fostering a data-driven culture. Building a strong data governance framework is also crucial, as it ensures the quality, consistency, and security of the data being used for decision-making. This section addresses the importance of data stewardship and compliance, which is particularly critical in today’s regulatory landscape. Next, we turn our attention to technology and infrastructure. From data warehousing and ETL (Extract, Transform, Load) processes to cloud-based BI solutions and real-time analytics, we cover the technologies that support BI platforms, and the steps involved in integrating and managing these tools within an organization’s infrastructure. The rapid adoption of cloud computing and big data technologies has redefined how businesses manage and process large volumes of data. This book discusses how to evaluate and implement the right mix of on-premises and cloud-based solutions, and how to scale BI environments to meet the growing needs of enterprise users. We also address the challenges of user adoption and training, which are often barriers to the successful implementation of BI solutions. We discuss best practices for engaging users across all levels of the organization and ensuring that BI tools are used effectively to inform decisions. Additionally, we explore how organizations can foster a culture that encourages data literacy and empowers individuals at all levels to leverage BI for strategic insights. Finally, this book covers advanced BI topics, such as AI-driven analytics, predictive and prescriptive modeling, and the integration of BI with machine learning and data science. As enterprises continue to evolve and their data environments become more sophisticated, the ability to incorporate advanced analytics and integrate BI with broader enterprise technologies will be key to gaining a competitive advantage. The objective of this book is not only to provide practical guidance for managing BI at an enterprise level but also to give readers a strategic understanding of how BI impacts organizational performance. Whether you oversee a BI department, a data management team, or a business unit, you will find actionable insights that will help you drive the adoption and success of your BI initiatives. In an era where data is the new oil, managing enterprise business intelligence is more critical than ever. This guide offers both a roadmap and practical solutions to empower businesses to unlock the full potential of their data and transform it into insights that lead to better decision-making, improved efficiency, and sustainable growth. Welcome to a journey of mastering enterprise Business Intelligence, unlocking its true potential, and transforming the way your organization uses data to stay competitive in the digital age. Authors |
| power bi nlp: Learning Microsoft Azure Jonah Carrio Andersson, 2023-11-20 If your organization plans to modernize services and move to the cloud from legacy software or a private cloud on premises, this book is for you. Software developers, solution architects, cloud engineers, and anybody interested in cloud technologies will learn fundamental concepts for cloud computing, migration, transformation, and development using Microsoft Azure. Author and Microsoft MVP Jonah Carrio Andersson guides you through cloud computing concepts and deployment models, the wide range of modern cloud technologies, application development with Azure, team collaboration services, security services, and cloud migration options in Microsoft Azure. You'll gain insight into the Microsoft Azure cloud services that you can apply in different business use cases, software development projects, and modern solutions in the cloud. You'll also become fluent with Azure cloud migration services, serverless computing technologies that help your development team work productively, Azure IoT, and Azure cognitive services that make your application smarter. This book also provides real-world advice and best practices based on the author's own Azure migration experience. Gain insight into which Azure cloud service best suits your company's particular needs Understand how to use Azure for different use cases and specific technical requirements Start developing cloud services, applications, and solutions in the Azure environment Learn how to migrate existing legacy applications to Microsoft Azure |
| power bi nlp: Mastering OSINT Cybellium, 2023-09-05 In an age defined by information abundance, the practice of Open Source Intelligence (OSINT) has emerged as a potent tool for uncovering insights hidden in plain sight. Mastering OSINT is an illuminating guide that equips readers with the skills and strategies needed to navigate the vast realm of open source information, enabling them to become adept OSINT practitioners capable of extracting valuable knowledge from the digital landscape. About the Book: Authored by leading experts in the field of OSINT, Mastering OSINT offers an in-depth exploration of the techniques, tools, and methodologies used to harness open source information effectively. Through a combination of real-world examples, case studies, and practical exercises, this book provides readers with the knowledge required to excel in the dynamic field of OSINT. Key Features: OSINT Fundamentals: The book begins by unraveling the foundational concepts of OSINT, guiding readers through the principles and ethics that underpin this powerful practice. Search Techniques: Readers will delve into advanced search techniques and strategies that optimize the collection of open source information from a variety of online sources. Social Media Analysis: With social media becoming a treasure trove of insights, the book explores methods for extracting actionable intelligence from platforms like Twitter, Facebook, LinkedIn, and more. Web Scraping and Automation: The book covers the art of web scraping and automation, empowering readers to gather, process, and analyze data at scale to uncover valuable insights. Digital Footprint Analysis: Through digital footprint analysis, readers will learn to piece together fragments of online presence to construct a comprehensive profile of individuals and organizations. Dark Web Exploration: In a world where hidden corners of the internet exist, the book sheds light on navigating the dark web to gather intelligence while maintaining security and anonymity. Investigative Techniques: From geolocation analysis to image forensics, the book equips readers with a toolkit of investigative techniques that enhance the quality and accuracy of OSINT findings. Case Studies and Practical Scenarios: Featuring real-world case studies and practical scenarios, readers gain firsthand insights into how OSINT techniques are applied to solve complex problems and uncover critical information. Who Should Read This Book: Mastering OSINT is a must-read for intelligence analysts, cybersecurity professionals, law enforcement personnel, journalists, researchers, and anyone seeking to harness the power of open source intelligence to gain a competitive edge or enhance security. Whether you're a novice curious about OSINT or a seasoned professional looking to refine your skills, this book serves as an essential guide to mastering the art of extracting insights from open sources. About the Authors: The authors of Mastering OSINT are esteemed practitioners and researchers in the field of open source intelligence. With a deep understanding of the nuances and challenges of OSINT, they share their wealth of knowledge, experience, and insights to empower readers to excel in the realm of open source intelligence. |
| power bi nlp: A Practical Guide to Hybrid Natural Language Processing Jose Manuel Gomez-Perez, Ronald Denaux, Andres Garcia-Silva, 2020-06-16 This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs. To this end, it first introduces the main building blocks and then describes how they can be integrated to support the effective implementation of real-world NLP applications. To illustrate the ideas described, the book also includes a comprehensive set of experiments and exercises involving different algorithms over a selection of domains and corpora in various NLP tasks. Throughout, the authors show how to leverage complementary representations stemming from the analysis of unstructured text corpora as well as the entities and relations described explicitly in a knowledge graph, how to integrate such representations, and how to use the resulting features to effectively solve NLP tasks in a range of domains. In addition, the book offers access to executable code with examples, exercises and real-world applications in key domains, like disinformation analysis and machine reading comprehension of scientific literature. All the examples and exercises proposed in the book are available as executable Jupyter notebooks in a GitHub repository. They are all ready to be run on Google Colaboratory or, if preferred, in a local environment. A valuable resource for anyone interested in the interplay between neural and knowledge-based approaches to NLP, this book is a useful guide for readers with a background in structured knowledge representations as well as those whose main approach to AI is fundamentally based on logic. Further, it will appeal to those whose main background is in the areas of machine and deep learning who are looking for ways to leverage structured knowledge bases to optimize results along the NLP downstream. |
| power bi nlp: Embedded Analytics Donald Farmer, Jim Horbury, 2023-05-15 Over the past 10 years, data analytics and data visualization have become essential components of an enterprise information strategy. And yet, the adoption of data analytics has remained remarkably static, reaching no more than 30% of potential users. This book explores the most important techniques for taking that adoption further: embedding analytics into the workflow of our everyday operations. Authors Donald Farmer and Jim Horbury show business users how to improve decision making without becoming analytics specialists. You'll explore different techniques for exchanging data, insights, and events between analytics platforms and hosting applications. You'll also examine issues including data governance and regulatory compliance and learn best practices for deploying and managing embedded analytics at scale. Learn how data analytics improves business decision making and performance Explore advantages and disadvantages of different embedded analytics platforms Develop a strategy for embedded analytics in an organization or product Define the architecture of an embedded solution Select vendors, platforms, and tools to implement your architecture Hire or train developers and architects to build the embedded solutions you need Understand how embedded analytics interacts with traditional analytics |
| power bi nlp: Emerging Developments and Technologies in Digital Government Guo, Yuanyuan, 2024-04-15 As the digital government field continues to evolve rapidly, scholars and professionals must stay ahead of the curve by developing innovative solutions and gaining comprehensive insights. The global landscape of digital governance is undergoing transformative shifts, necessitating a deep understanding of historical developments, current practices, and emerging trends. This urgent demand for knowledge forms the crux of the problem that the book, Emerging Developments and Technologies in Digital Government, addresses with expert knowledge and insights. The book serves as an indispensable resource for academic scholars grappling with the complexities of digital government. It critically examines historical transitions from technology-centric paradigms to people-centric models, shedding light on the global impact of open data initiatives and the vital role of human-computer interaction in reshaping government websites. For professionals and researchers across disciplines such as library sciences, administrative management, sociology, and information technology, this book becomes a beacon, offering insights and tangible solutions to navigate the multifaceted dimensions of digital government. |
| power bi nlp: Practical Natural Language Processing Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, Harshit Surana, 2020-06-17 Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective |
| power bi nlp: Deep Learning Dr. C. Thangamani, Ms. V.Anuradha, Mrs. R. Arivukkodi, Dr. R.Amudhevalli, 2024-10-28 Deep Learning is a artificial neural networks and their application to machine learning. The foundational concepts, techniques, and algorithms that drive deep learning, providing both theoretical insights and practical implementation strategies. It covers various architectures such as convolutional and recurrent networks, deep reinforcement learning, and unsupervised learning, while also addressing challenges like overfitting, model interpretability, and optimization. Suitable for both beginners and advanced learners, it offers a solid foundation in understanding and applying deep learning in real-world scenarios. |
| power bi nlp: AI-Powered Productivity Asma Asfour, 2024-08-06 AI-Powered Productivity is a guide to understanding and using AI and generative tools in professional settings. Chapter 1 introduces AI basics, its impact on various sectors, and an overview of generative AI tools. Chapter 2 delves into large language models exploring their integration with multimodal technologies and effects on productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, with tutorials on crafting effective prompts and advanced techniques, including real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision-making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights AI's role in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future workforce trends. This book is designed for both beginners and professionals, offering a deep dive into AI concepts, tools, and practices that define the current AI landscape. |
| power bi nlp: Learning AI Tools in Tableau Ann Jackson, 2025-01-14 As businesses increasingly rely on data to drive decisions, the role of advanced analytics and AI in enhancing data interpretation is becoming crucial. For professionals tasked with optimizing data analytics platforms like Tableau, staying ahead of the curve with the latest tools isn't just beneficial—it's essential. This insightful guide takes you through the integration of Tableau Pulse and Einstein Copilot, explaining their roles within the broader Tableau and Salesforce ecosystems. Author Ann Jackson, an esteemed analytics professional with a deep expertise in Tableau, offers a step-by-step exploration of these tools, backed by real-world use cases that demonstrate their impact across various industries. By the end of this book, you will: Understand the functionalities of Tableau Pulse and Einstein Copilot and how to use them Learn to deploy Tableau Pulse effectively, ensuring it aligns with your business objectives Navigate discussions on AI's role within Tableau, enhancing your strategic conversations Visualize how Tableau Pulse operates through detailed images and scenarios Utilize Einstein Copilot in Tableau Desktop/Prep to streamline and enhance data analysis |
| power bi nlp: Building Intelligent Applications with Generative AI Yattish Ramhorry, 2024-08-22 DESCRIPTION Building Intelligent Applications with Generative AI is a comprehensive guide that unlocks the power of generative AI for building cutting-edge applications. This book covers a wide range of use cases and practical examples, from text generation and conversational agents to creative media generation and code completion. These examples are designed to help you capitalize on the potential of generative AI in your applications. Through clear explanations, step-by-step tutorials, and real-world case studies, you will learn how to prepare data and train generative AI models. You will also explore different generative AI techniques, including large language models like GPT-4, ChatGPT, Llama 2, and Google’s Gemini, to understand how they can be applied in various domains, such as content generation, virtual assistants, and code generation. With a focus on practical implementation, this book also examines ethical considerations, best practices, and future trends in generative AI. Further, this book concludes by exploring ethical considerations and best practices for building responsible GAI applications, ensuring you are harnessing this technology for good. By the end of this book, you will be well-equipped to leverage the power of GAI to build intelligent applications and unleash your creativity in innovative ways. KEY FEATURES ● Learn the fundamentals of generative AI and the practical usage of prompt engineering. ● Gain hands-on experience in building generative AI applications. ● Learn to use tools like LangChain, LangSmith, and FlowiseAI to create intelligent applications and AI chatbots. WHAT YOU WILL LEARN ● Understand generative AI (GAI) and large language models (LLMs). ● Explore real-world GAI applications across industries. ● Build intelligent applications with the ChatGPT API. ● Explore retrieval augmented generation with LangChain and Gemini Pro. ● Create chatbots with LangChain and Streamlit for data retrieval. WHO THIS BOOK IS FOR This book is for developers, data scientists, AI practitioners, and tech enthusiasts who are interested in leveraging generative AI techniques to build intelligent applications across various domains. TABLE OF CONTENTS 1. Exploring the World of Generative AI 2. Use Cases for Generative AI Applications 3. Mastering the Art of Prompt Engineering 4. Integrating Generative AI Models into Applications 5. Emerging Trends and the Future of Generative AI 6. Building Intelligent Applications with the ChatGPT API 7. Retrieval Augmented Generation with Gemini Pro 8. Generative AI Applications with Gradio 9. Visualize your Data with LangChain and Streamlit 10. Building LLM Applications with Llama 2 11. Building an AI Document Chatbot with Flowise AI 12. Best Practices for Building Applications with Generative AI 13. Ethical Considerations of Generative AI |
| power bi nlp: Natural Language Processing with Python Quick Start Guide Nirant Kasliwal, 2018-11-30 Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key Features A no-math, code-driven programmer's guide to text processing and NLP Get state of the art results with modern tooling across linguistics, text vectors and machine learning Fundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorch Book Description NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges. What you will learn Understand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpus Work with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clustering Deep Learning in NLP using PyTorch with a code-driven introduction to PyTorch Using an NLP project management Framework for estimating timelines and organizing your project into stages Hack and build a simple chatbot application in 30 minutes Deploy an NLP or machine learning application using Flask as RESTFUL APIs Who this book is for Programmers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory. |
| power bi nlp: Data-Driven Business Intelligence Systems for Socio-Technical Organizations Keikhosrokiani, Pantea, 2024-04-09 The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers. |
| power bi nlp: The Natural Language Processing Workshop Rohan Chopra, Aniruddha M. Godbole, Nipun Sadvilkar, 2020-07 The Natural Language Processing Workshop takes you through fundamental NLP techniques, such as preparing datasets, collecting text, extracting text, and sentiment analysis. As you progress, you'll get to grips with creating your own chatbots and dynamic models. |
| power bi nlp: Natural Language Processing for Social Media Anna Atefeh Farzindar, Diana Inkpen, 2020-04-10 In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF). In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data. |
| power bi nlp: Applied Data Science in Tourism Roman Egger, 2022-01-31 Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a how-to approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau |
| power bi nlp: AI-Enhanced Teaching Methods Ahmed, Zeinab E., Hassan, Aisha A., Saeed, Rashid A., 2024-04-22 The digital age has ushered in an era where students must be equipped not only with traditional knowledge but also with the skills to navigate an increasingly interconnected and technologically driven world. As traditional teaching methods encounter the complexities of the 21st century, the demand for innovation becomes more apparent. This paves the way for the era of artificial intelligence (AI), a technological frontier that carries the potential to reshape education fundamentally. AI-Enhanced Teaching Methods recognizes the urgency of the ongoing technological shift and delves into an exploration of how AI can be effectively harnessed to redefine the learning experience. The book serves as a guide for educators, offering insights into navigating between conventional teaching methodologies and the possibilities presented by AI. It provides an understanding of AI's role in education, covering topics from machine learning to natural language processing. Ethical considerations, including privacy and bias, are thoroughly addressed with thoughtful solutions as well. Additionally, the book provides valuable support for administrators, aiding in the integration of these technologies into existing curricula. |
| power bi nlp: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| power bi nlp: Proceedings of the International Conference on Innovation & Entrepreneurship in Computing, Engineering & Science Education (InvENT 2024) Nur Atiqah Sia Abdullah, Teoh Sian Hoon, Nurshamshida Md Shamsudin, Rafeah Legino, 2024-11-29 This is an open access book. Universiti Teknologi MARA is proud to host the International Conference on Innovation and Entrepreneurship in Computing, Engineering, and Science Education 2024, or in short, InvENT2024, a signature programme of the Asia Technological University Network (ATU-Net), which was inaugurated in 2023 in Brunei. This event will also be co-hosted by the University of Science and Technology of the Southern Philippine (USTP). The event will be held in Shah Alam, the capital of Selangor, between 20 and 22 August 2024. The theme of the event is Converging Innovation with Soul: AI in Entrepreneurship, Technology, and Education. The theme was selected in accordance with the growing concern about the fast-growing development of AI, which has now transcended almost every aspect of living. The AI industry itself is said to be a capital that can boost the Malaysian economy. As it grows, it raises questions about itself and our future in this world. This event is therefore set up as a platform that will collate information from academics, industry, and government sectors through powerful speeches, informative exhibitions, and paper presentations on AI use and development in computing, engineering, science, and entrepreneurship. A special highlight will be the plenary on the first day and the officiating speech by the Malaysian Prime Minister, the YAB Dato’ Seri Anwar Ibrahim, whose speech will be about integrating and guiding AI into civilized society as prescribed in Malaysia’s National Artificial Intelligence (AI) Roadmap 2021-2025. The second-day plenary will be by a well-known and much-respected AI proponent and editor-in-chief of a few respected peer-reviewed journals, Prof. Dr. Hamido Fujita, who will be talking about AI technology, innovation, application, and education. Join us to learn more about AI. |
| power bi nlp: ADMINISTRATION IN 2025 No More Busywork Jens Belner, Unlock Your Organization’s Potential with AI-Driven Automation Are you tired of spending endless hours on tedious administrative tasks? Looking for a way to transform your organization into a hub of efficiency and productivity? Look no further. “Streamlining Administrative Tasks Through AI-Driven Automation” is the essential guide that will revolutionize how you work. Why You Need This Book In today’s fast-paced business environment, efficiency is key. This book covers everything you need to know to harness the power of Artificial Intelligence and automate your administrative processes. Here’s what you will discover: Comprehensive Insights into Administrative Work Understanding the Current Landscape: Gain a clear perspective on the challenges facing today’s administrative workforce. Importance of Efficiency: Learn why streamlining tasks is crucial for modern organizations. Embracing the Rise of AI Historical Context: Understand the evolution of automation in business. AI in the Workplace: Explore the current capabilities of AI technology in improving work environments. Mastering Key Administrative Tasks Smart Email Management: Implement techniques for effective email filtering and AI-driven auto-responses. Document Creation: Discover how to streamline your drafting processes and collaborate in real-time using AI tools. Organizational Excellence: Automate your document filing and retrieval for optimal efficiency. Elevating Communication and Scheduling AI for Communication: Utilize AI to schedule meetings, manage calendars, and send automated invitations. Enhancing Team Collaboration: Leverage AI-driven task management tools to assign and track responsibilities effortlessly. Optimizing Business Processes Lead Handling & Sales Optimization: Accelerate your lead qualification processes and personalize customer interactions through automation. Cost Savings: Analyze the financial benefits of implementing AI solutions and reallocate resources for maximum efficiency. Risk Management: Utilize AI for compliance monitoring and anomaly detection to minimize errors. Future-Proofing Your Organization Scalability: Learn how AI can adapt to your organization’s growth and planning needs. Training & Onboarding: Develop effective programs to ensure successful user adoption of AI tools. Future Trends: Stay ahead of the curve by understanding evolving AI technologies in the workplace. Key Takeaways In the book’s conclusion, you’ll find actionable next steps to begin your journey toward a more efficient organization through AI-driven automation. Ready to Transform Your Organization? Don’t let administrative tasks hold you back. “Streamlining Administrative Tasks Through AI-Driven Automation” is your roadmap to increased productivity, enhanced teamwork, and a smarter, more efficient workplace. Unlock the potential of AI and watch your organization thrive! Get your copy today and start transforming the way you work. |
| power bi nlp: Natural Language Processing for Social Media, Third Edition Anna Atefeh Farzindar, Diana Inkpen, 2022-05-31 In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF). In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data. |
| power bi nlp: AI Simplified: Harnessing Microsoft Technologies for Cost-Effective Artificial Intelligence Solutions Keith Baldwin, 2024-11-18 AI Simplified: Harnessing Microsoft Technologies for Cost-Effective Artificial Intelligence Solutions is your practical guide to unlocking the power of AI within your organization without breaking the bank or hiring new specialized teams. Tailored for business leaders, executives, managers, and technical professionals, this book demystifies AI and provides actionable steps to integrate AI solutions effectively using tools and platforms you already know. What You'll Learn: Grasp essential AI concepts and terminologies without getting lost in complex algorithms. Discover how AI can revolutionize your business operations by automating tasks, optimizing decision-making, and enhancing customer interactions. Form an effective AI Innovation Team, leveraging the skills of your existing developers and infrastructure. Explore practical use cases across various industries, from customer service automation to data-driven insights. Develop AI prototypes, then minimally viable products, quickly and iterate efficiently. Navigate and leverage Microsoft's AI ecosystem, including Power Platform, CoPilot, and Azure, while comparing other options like AWS and Google AI. Why This Book Stands Out: Cost-Effective Strategies: Learn how to develop and deploy AI applications without massive expenses or high risk. Step-by-Step Guidance: Follow an iterative approach to AI development, reducing costs and minimizing the risk of failure. Actionable Resources: Gain access to working AI prototype code, practical examples, and a roadmap that keeps your team aligned and moving forward. Whether you're just beginning your AI journey or looking to expand your knowledge, AI Simplified provides the foundation you need to start transforming your business into an AI-driven enterprise efficiently and affordably. Join us on this journey to smarter, more efficient business operations! For more resources and to connect with the author, visit AInDotNet.com. |
| power bi nlp: Natural Language Processing in Action Hannes Hapke, Cole Howard, Hobson Lane, 2019-03-16 Summary Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before. About the Book Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions. What's inside Some sentences in this book were written by NLP! Can you guess which ones? Working with Keras, TensorFlow, gensim, and scikit-learn Rule-based and data-based NLP Scalable pipelines About the Reader This book requires a basic understanding of deep learning and intermediate Python skills. About the Author Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production. Table of Contents PART 1 - WORDY MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization) Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 - DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving retention with long short-term memory networks Sequence-to-sequence models and attention PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction (named entity extraction and question answering) Getting chatty (dialog engines) Scaling up (optimization, parallelization, and batch processing) |
| power bi nlp: Excel Formulas Unleashed: Advanced Techniques for All Users Daniel Evans, 2024-12-11 Delve into the enigmatic world of Excel with this comprehensive guide that will unlock the boundless potential of its formulas. Excel Formulas Unleashed is not just another technical manual; it's an indispensable companion for users of all levels who aspire to harness the true power of spreadsheets. Within its pages, you'll discover an arsenal of advanced techniques that will transform your ability to manipulate data, analyze complex scenarios, and automate tasks with unparalleled efficiency. Prepare to unleash the true potential of Excel with this extraordinary guide. We've meticulously crafted it to empower you with an arsenal of advanced formulas that will elevate your spreadsheet prowess. Whether you're a seasoned pro or a novice yearning to unlock Excel's hidden depths, this book is your gateway to mastering its formulaic capabilities. This comprehensive guide is meticulously designed to meet the needs of users across the spectrum. From absolute beginners to seasoned spreadsheet enthusiasts, Excel Formulas Unleashed provides a structured learning path that caters to your unique skill level. Immerse yourself in the intricacies of Excel's formula syntax, unravel the mysteries of complex functions, and witness firsthand how formulas can transform raw data into actionable insights. Discover the power of Excel formulas to automate repetitive tasks, streamline data analysis, and unlock hidden patterns within your spreadsheets. This guide will equip you with an arsenal of advanced techniques that will transform the way you work with Excel. Whether you're a seasoned professional or just starting your journey with spreadsheets, Excel Formulas Unleashed is the ultimate resource to maximize your productivity and efficiency. |
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Players win a prize by matching one of the 9 ways to win. The jackpot is won by matching all five white balls in any order and the red Powerball. Jackpot …
Power (physics) - Wikipedia
Power is the amount of energy transferred or converted per unit time. In the International System of Units, the unit of power is the watt, equal to …
POWER Definition & Meaning - Merriam-Webster
The meaning of POWER is ability to act or produce an effect. How to use power in a sentence. Synonym Discussion …
POWER | definition in the Cambridge English Dictionary
POWER meaning: 1. ability to control people and events: 2. the amount of political control a person or group …
POWER definition in American English | Collins English Dicti…
Power is energy, especially electricity, that is obtained in large quantities from a fuel source and used to operate lights, heating, and machinery.
Home | Powerball
Players win a prize by matching one of the 9 ways to win. The jackpot is won by matching all five white balls in any order and the red Powerball. Jackpot winners may choose to receive their …
Power (physics) - Wikipedia
Power is the amount of energy transferred or converted per unit time. In the International System of Units, the unit of power is the watt, equal to one joule per second. Power is a scalar quantity.
POWER Definition & Meaning - Merriam-Webster
The meaning of POWER is ability to act or produce an effect. How to use power in a sentence. Synonym Discussion of Power.
POWER | definition in the Cambridge English Dictionary
POWER meaning: 1. ability to control people and events: 2. the amount of political control a person or group has…. Learn more.
POWER definition in American English | Collins English Dictionary
Power is energy, especially electricity, that is obtained in large quantities from a fuel source and used to operate lights, heating, and machinery.
Power - Math is Fun
Power is energy flowing! It is measured as energy per unit of time. No, not that type of Power Formula! Power is the rate of energy per time: Example: 3000 J of energy is used in 20 …
What is Power? - BYJU'S
What is Power? We can define power as the rate of doing work, it is the work done in unit time. The SI unit of power is Watt (W) which is joules per second (J/s). Sometimes the power of …
Power (Physics): Definition, Formula, Units, How To Find (W
Dec 28, 2020 · Power is a measure of how much work is done in a time interval. A quick note on horsepower: The term is meant to compare the output of a steam engine to that of a horse, as …
Power – The Physics Hypertextbook
Power is the rate at which work is done (or energy is transferred). What is the unit of power? Watt is the unit of power!
Power Definition & Meaning | Britannica Dictionary
POWER meaning: 1 : the ability or right to control people or things often + over; 2 : political control of a country or area
