Advertisement
| mastering julia 1.0: Mastering Julia Malcolm Sherrington, 2015-07-22 Julia is a well-constructed programming language with fast execution speed, eliminating the classic problem of performing analysis in one language and translating it for performance into a second. This book will help you develop and enhance your programming skills in Julia to solve real-world automation challenges. This book starts off with a refresher on installing and running Julia on different platforms. Next, you will compare the different ways of working with Julia and explore Julia's key features in-depth by looking at design and build. You will see how data works using simple statistics and analytics, and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks and observe how Julia can cooperate with external processes in order to enhance graphics and data visualization. Finally, you will look into meta-programming and learn how it adds great power to the language and establish networking and distributed computing with Julia. |
| mastering julia 1.0: Learning Julia Anshul Joshi, Rahul Lakhanpal, 2017-11-24 Learn Julia language for data science and data analytics About This Book Set up Julia's environment and start building simple programs Explore the technical aspects of Julia and its potential when it comes to speed and data processing Write efficient and high-quality code in Julia Who This Book Is For This book allows existing programmers, statisticians and data scientists to learn the Julia and take its advantage while building applications with complex numerical and scientific computations. Basic knowledge of mathematics is needed to understand the various methods that will be used or created in the book to exploit the capabilities for which Julia is made. What You Will Learn Understand Julia's ecosystem and create simple programs Master the type system and create your own types in Julia Understand Julia's type system, annotations, and conversions Define functions and understand meta-programming and multiple dispatch Create graphics and data visualizations using Julia Build programs capable of networking and parallel computation Develop real-world applications and use connections for RDBMS and NoSQL Learn to interact with other programming languages–C and Python—using Julia In Detail Julia is a highly appropriate language for scientific computing, but it comes with all the required capabilities of a general-purpose language. It allows us to achieve C/Fortran-like performance while maintaining the concise syntax of a scripting language such as Python. It is perfect for building high-performance and concurrent applications. From the basics of its syntax to learning built-in object types, this book covers it all. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Julia to explore its wide and ever-growing package ecosystem and also for experienced developers/statisticians/data scientists who want to add Julia to their skill-set. The book presents the fundamentals of programming in Julia and in-depth informative examples, using a step-by-step approach. You will be taken through concepts and examples such as doing simple mathematical operations, creating loops, metaprogramming, functions, collections, multiple dispatch, and so on. By the end of the book, you will be able to apply your skills in Julia to create and explore applications of any domain. Style and approach This book demonstrates the basics of Julia along with some data structures and testing tools that will give you enough material to get started with the language from an application standpoint. |
| mastering julia 1.0: Julia High Performance Avik Sengupta, 2016-04-26 Design and develop high performing programs with Julia About This Book Learn to code high reliability and high performance programs Stand out from the crowd by developing code that runs faster than your peers' codes This book is intended for developers who are interested in high performance technical programming. Who This Book Is For This book is for beginner and intermediate Julia programmers who are interested in high performance technical computing. You will have a basic familiarity with Julia syntax, and have written some small programs in the language. What You Will Learn Discover the secrets behind Julia's speed Get a sense of the possibilities and limitations of Julia's performance Analyze the performance of Julia programs Measure the time and memory taken by Julia programs Create fast machine code using Julia's type information Define and call functions without compromising Julia's performance Understand number types in Julia Use Julia arrays to write high performance code Get an overview of Julia's distributed computing capabilities In Detail Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia. You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia's design makes them fast. The last chapter will give you a taste of Julia's distributed computing capabilities. Style and approach This is a hands-on manual that will give you good explanations about the important concepts related to Julia programming. |
| mastering julia 1.0: Julia Programming for Operations Research Changhyun Kwon, 2019-03-03 Last Updated: December 2020 Based on Julia v1.3+ and JuMP v0.21+ The main motivation of writing this book was to help the author himself. He is a professor in the field of operations research, and his daily activities involve building models of mathematical optimization, developing algorithms for solving the problems, implementing those algorithms using computer programming languages, experimenting with data, etc. Three languages are involved: human language, mathematical language, and computer language. His team of students need to go over three different languages, which requires translation among the three languages. As this book was written to teach his research group how to translate, this book will also be useful for anyone who needs to learn how to translate in a similar situation. The Julia Language is as fast as C, as convenient as MATLAB, and as general as Python with a flexible algebraic modeling language for mathematical optimization problems. With the great support from Julia developers, especially the developers of the JuMP—Julia for Mathematical Programming—package, Julia makes a perfect tool for students and professionals in operations research and related areas such as industrial engineering, management science, transportation engineering, economics, and regional science. For more information, visit: http://www.chkwon.net/julia |
| mastering julia 1.0: Hands-On Design Patterns and Best Practices with Julia Tom Kwong, 2020-01-17 Design and develop high-performance, reusable, and maintainable applications using traditional and modern Julia patterns with this comprehensive guide Key FeaturesExplore useful design patterns along with object-oriented programming in Julia 1.0Implement macros and metaprogramming techniques to make your code faster, concise, and efficientDevelop the skills necessary to implement design patterns for creating robust and maintainable applicationsBook Description Design patterns are fundamental techniques for developing reusable and maintainable code. They provide a set of proven solutions that allow developers to solve problems in software development quickly. This book will demonstrate how to leverage design patterns with real-world applications. Starting with an overview of design patterns and best practices in application design, you'll learn about some of the most fundamental Julia features such as modules, data types, functions/interfaces, and metaprogramming. You'll then get to grips with the modern Julia design patterns for building large-scale applications with a focus on performance, reusability, robustness, and maintainability. The book also covers anti-patterns and how to avoid common mistakes and pitfalls in development. You'll see how traditional object-oriented patterns can be implemented differently and more effectively in Julia. Finally, you'll explore various use cases and examples, such as how expert Julia developers use design patterns in their open source packages. By the end of this Julia programming book, you'll have learned methods to improve software design, extensibility, and reusability, and be able to use design patterns efficiently to overcome common challenges in software development. What you will learnMaster the Julia language features that are key to developing large-scale software applicationsDiscover design patterns to improve overall application architecture and designDevelop reusable programs that are modular, extendable, performant, and easy to maintainWeigh up the pros and cons of using different design patterns for use casesExplore methods for transitioning from object-oriented programming to using equivalent or more advanced Julia techniquesWho this book is for This book is for beginner to intermediate-level Julia programmers who want to enhance their skills in designing and developing large-scale applications. |
| mastering julia 1.0: Mastering the Art of French Cooking, Volume 1 Julia Child, Louisette Bertholle, Simone Beck, 1983-09-12 NEW YORK TIMES BESTSELLER • The definitive cookbook on French cuisine for American readers: What a cookbook should be: packed with sumptuous recipes, detailed instructions, and precise line drawings. Some of the instructions look daunting, but as Child herself says in the introduction, 'If you can read, you can cook.' —Entertainment Weekly “I only wish that I had written it myself.” —James Beard Featuring 524 delicious recipes and over 100 instructive illustrations to guide readers every step of the way, Mastering the Art of French Cooking offers something for everyone, from seasoned experts to beginners who love good food and long to reproduce the savory delights of French cuisine. Julia Child, Simone Beck, and Louisette Bertholle break down the classic foods of France into a logical sequence of themes and variations rather than presenting an endless and diffuse catalogue of dishes—from historic Gallic masterpieces to the seemingly artless perfection of a dish of spring-green peas. Throughout, the focus is on key recipes that form the backbone of French cookery and lend themselves to an infinite number of elaborations—bound to increase anyone’s culinary repertoire. “Julia has slowly but surely altered our way of thinking about food. She has taken the fear out of the term ‘haute cuisine.’ She has increased gastronomic awareness a thousandfold by stressing the importance of good foundation and technique, and she has elevated our consciousness to the refined pleasures of dining. —Thomas Keller, The French Laundry |
| mastering julia 1.0: Julia High Performance Avik Sengupta, 2019-06-11 |
| mastering julia 1.0: Dearie Bob Spitz, 2013-04-23 NATIONAL BESTSELLER • Arollicking biography (People Magazine) and extraordinarily entertaining account of how Julia Child transformed herself into the cult figure who touched off a food revolution that has gripped the country for decades. Spanning Pasadena to Paris, acclaimed author Bob Spitz reveals the history behind the woman who taught America how to cook. A genuine rebel who took the pretensions that embellished French cuisine and fricasseed them to a fare-thee-well, paving the way for a new era of American food—not to mention blazing a new trail in television—Child redefined herself in middle age, fought for women’s rights, and forever altered how we think about what we eat. Chronicling Julia's struggles, her heartwarming romance with Paul, and, of course, the publication of Mastering the Art of French Cooking and her triumphant TV career, Dearie is a stunning story of a truly remarkable life. |
| mastering julia 1.0: Mastering the Art of French Eating Ann Mah, 2013-09-26 The memoir of a young diplomat’s wife who must reinvent her dream of living in Paris—one dish at a time When journalist Ann Mah’s diplomat husband is given a three-year assignment in Paris, Ann is overjoyed. A lifelong foodie and Francophile, she immediately begins plotting gastronomic adventures à deux. Then her husband is called away to Iraq on a year-long post—alone. Suddenly, Ann’s vision of a romantic sojourn in the City of Light is turned upside down. So, not unlike another diplomatic wife, Julia Child, Ann must find a life for herself in a new city. Journeying through Paris and the surrounding regions of France, Ann combats her loneliness by seeking out the perfect pain au chocolat and learning the way the andouillette sausage is really made. She explores the history and taste of everything from boeuf Bourguignon to soupe au pistou to the crispiest of buckwheat crepes. And somewhere between Paris and the south of France, she uncovers a few of life’s truths. Like Sarah Turnbull’s Almost French and Julie Powell’s New York Times bestseller Julie and Julia, Mastering the Art of French Eating is interwoven with the lively characters Ann meets and the traditional recipes she samples. Both funny and intelligent, this is a story about love—of food, family, and France. |
| mastering julia 1.0: Statistics with Julia Yoni Nazarathy, Hayden Klok, 2021-09-04 This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia. |
| mastering julia 1.0: Julia Child & Company Julia Child, E. S. Yntema, 1978 Features recipes that will be shown on Child's new series in addition to presenting dishes and alternate selections for thirteen meals she has matched up with different types of guests |
| mastering julia 1.0: Mastering the Art of Julia Programming: Advanced Techniques for Expert-Level Programming Steve Jones, 2025-02-16 Mastering the Art of Julia Programming: Advanced Techniques for Expert-Level Programming is the definitive guide for seasoned developers seeking to elevate their proficiency in Julia. This book goes beyond conventional programming instruction, diving deeply into the intricacies of the Julia language. Through meticulously crafted chapters, readers will explore complex topics such as the type system, metaprogramming, performance optimization, and effective error handling. Each section is designed to build upon the last, offering a logical progression that ensures comprehensive understanding and mastery of advanced Julia concepts. This book equips readers with the practical skills necessary to apply advanced techniques in real-world scenarios. With an emphasis on pragmatic, hands-on learning, it presents readers with detailed examples and case studies, demonstrating how to implement high-performance solutions in diverse computational contexts. Whether it's developing sophisticated machine learning models, constructing robust concurrent applications, or optimizing mathematical computations, this guide presents strategies and tools that enable programmers to maximize their efficiency and creativity. Mastering the Art of Julia Programming is not only an invaluable resource for individual programmers but also an asset for teams and organizations looking to foster a deeper understanding of Julia's capabilities. It prepares developers to contribute meaningfully to the Julia ecosystem by providing insights into effective package development and management. This book is an essential addition to the libraries of forward-thinking developers who aim to leverage Julia's potential to its fullest, ensuring they are at the cutting edge of programming technology. |
| mastering julia 1.0: Python for Finance Yves J. Hilpisch, 2018-12-05 The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks. |
| mastering julia 1.0: Introduction to Data Science Laura Igual, Santi Seguí, 2017-02-22 This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website. |
| mastering julia 1.0: Python for Scientists John M. Stewart, 2017-07-20 Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively. |
| mastering julia 1.0: Resilience Steven M. Southwick, Dennis S. Charney, Jonathan M. DePierro, 2023-09-07 Life presents us all with challenges. Most of us at some point will be struck by major traumas such as the sudden death of a loved one, a debilitating disease, or a natural disaster. What differentiates us is how we respond. In this important book, three experts in trauma and resilience answer key questions such as What helps people adapt to life's most challenging situations?, How can you build up your own resilience?, and What do we know about the science of resilience? Combining cutting-edge scientific research with the personal experiences of individuals who have survived some of the most traumatic events imaginable, including the COVID-19 pandemic, this book provides a practical resource that can be used time and time again. The experts describe ten key resilience factors, including facing fear, optimism, and relying on role models, through the experiences and personal reflections of highly resilient survivors. Each resilience factor will help you to adapt and grow from stressful life events and will bring hope and inspiration for overcoming adversity. |
| mastering julia 1.0: Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages Tanmay Bakshi, 2019-12-06 Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. A quick guide to start writing your own fun and useful Julia apps—no prior experience required! This engaging guide shows, step by step, how to build custom programs using Julia, the open-source, intuitive scripting language. Written by 15-year-old technology phenom Tanmay Bakshi, the book is presented in an accessible style that makes learning easy and enjoyable. Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages clearly explains the basics of Julia programming and takes a look at cutting-edge machine learning applications. You will also discover how to interface your Julia apps with code written in Python. Inside, you’ll learn to: • Set up and configure your Julia environment • Get up and running writing your own Julia apps • Define variables and use them in your programs • Use conditions, iterations, for-loops, and while-loops • Create, go through, and modify arrays • Build an app to manage things you lend and get back from your friends • Create and utilize dictionaries • Simplify maintenance of your code using functions • Apply functions on arrays and use functions recursively and generically • Understand and program basic machine learning apps |
| mastering julia 1.0: Julie and Julia Julie Powell, 2014-05-10 Nearing 30 and trapped in a dead-end secretarial job, Julie Powell reclaims her life by cooking every single recipe in Julia Child's legendary Mastering the Art of French Cooking in the span of one year. It's a hysterical, inconceivable redemptive journey - life rediscovered through aspics, calves' brains and crEme brUlEe. The bestselling memoir that's irresistible...A kind of Bridget Jones meets The French Chef (Philadelphia Inquirer) is now a major motion picture directed by Nora Ephron, starring Amy Adams as Julie and Meryl Streep as Julia, the film Julie & Julia will be released by Sony Pictures on August 7, 2009. |
| mastering julia 1.0: Mastering Qt 5 Guillaume Lazar, Robin Penea, 2016-12-15 Master application development by writing succinct, robust, and reusable code with Qt 5 About This Book Unleash the power of Qt 5 with C++14 Integrate useful third-party libraries such as OpenCV Package and deploy your application on multiple platforms Who This Book Is For This book will appeal to developers and programmers who would like to build GUI-based applications. Knowledge of C++ is necessary and the basics of Qt would be helpful. What You Will Learn Create stunning UIs with Qt Widget and Qt Quick Develop powerful, cross-platform applications with the Qt framework Design GUIs with the Qt Designer and build a library in it for UI preview Handle user interaction with the Qt signal/slot mechanism in C++ Prepare a cross-platform project to host a third-party library Build a Qt application using the OpenCV API Use the Qt Animation framework to display stunning effects Deploy mobile apps with Qt and embedded platforms In Detail Qt 5.7 is an application development framework that provides a great user experience and develops full-capability applications with Qt Widgets, QML, and even Qt 3D. This book will address challenges in successfully developing cross-platform applications with the Qt framework. Cross-platform development needs a well-organized project. Using this book, you will have a better understanding of the Qt framework and the tools to resolve serious issues such as linking, debugging, and multithreading. Your journey will start with the new Qt 5 features. Then you will explore different platforms and learn to tame them. Every chapter along the way is a logical step that you must take to master Qt. The journey will end in an application that has been tested and is ready to be shipped. Style and approach This is an easy-to-follow yet comprehensive guide to building applications in Qt. Each chapter covers increasingly advanced topics, with subjects grouped according to their complexity as well as their usefulness. Packed with practical examples and explanations, Mastering Qt contains everything you need to take your applications to the next level. |
| mastering julia 1.0: R for Data Science Hadley Wickham, Garrett Grolemund, 2016-12-12 Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true signals in your dataset Communicate—learn R Markdown for integrating prose, code, and results |
| mastering julia 1.0: IPython Interactive Computing and Visualization Cookbook Cyrille Rossant, 2014-09-25 Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods. |
| mastering julia 1.0: Julia 1.0 Programming Complete Reference Guide Ivo Balbaert, Adrian Salceanu, 2019-05-20 Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key FeaturesLeverage Julia's high speed and efficiency to build fast, efficient applicationsPerform supervised and unsupervised machine learning and time series analysisTackle problems concurrently and in a distributed environmentBook Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo BalbaertJulia Programming Projects by Adrian SalceanuWhat you will learnCreate your own types to extend the built-in type systemVisualize your data in Julia with plotting packagesExplore the use of built-in macros for testing and debuggingIntegrate Julia with other languages such as C, Python, and MATLABAnalyze and manipulate datasets using Julia and DataFramesDevelop and run a web app using Julia and the HTTP packageBuild a recommendation system using supervised machine learningWho this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must. |
| mastering julia 1.0: Introduction to Probability Joseph K. Blitzstein, Jessica Hwang, 2014-07-24 Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version. The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces. The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment. |
| mastering julia 1.0: Python for Data Analysis Wes McKinney, 2017-09-25 Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples |
| mastering julia 1.0: Mastering Differential Equations Teaching Company, 2011 In this course, Boston University Professor Robert L. Devaney presents an introduction to differential equations. |
| mastering julia 1.0: Prometheus: Up & Running Brian Brazil, 2018-07-09 Get up to speed with Prometheus, the metrics-based monitoring system used by tens of thousands of organizations in production. This practical guide provides application developers, sysadmins, and DevOps practitioners with a hands-on introduction to the most important aspects of Prometheus, including dashboarding and alerting, direct code instrumentation, and metric collection from third-party systems with exporters. This open source system has gained popularity over the past few years for good reason. With its simple yet powerful data model and query language, Prometheus does one thing, and it does it well. Author and Prometheus developer Brian Brazil guides you through Prometheus setup, the Node exporter, and the Alertmanager, then demonstrates how to use them for application and infrastructure monitoring. Know where and how much to apply instrumentation to your application code Identify metrics with labels using unique key-value pairs Get an introduction to Grafana, a popular tool for building dashboards Learn how to use the Node Exporter to monitor your infrastructure Use service discovery to provide different views of your machines and services Use Prometheus with Kubernetes and examine exporters you can use with containers Convert data from other monitoring systems into the Prometheus format |
| mastering julia 1.0: Dive Into Deep Learning Joanne Quinn, Joanne McEachen, Michael Fullan, Mag Gardner, Max Drummy, 2019-07-15 The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself. |
| mastering julia 1.0: Advanced Julia Programming: Comprehensive Techniques and Best Practices Adam Jones, 2024-12-11 Unlock the full potential of Julia, the high-performance language designed for technical computing, with Advanced Julia Programming: Comprehensive Techniques and Best Practices. This book serves as an essential resource for both newcomers and seasoned developers eager to deepen their understanding and enhance their skills in Julia. Advanced Julia Programming: Comprehensive Techniques and Best Practices provides an in-depth exploration of Julia’s features, sophisticated programming paradigms, and real-world applications. From mastering Julia's syntax and package ecosystem to exploring advanced topics like functional programming, concurrent and parallel computing, and web application development, this book leaves no stone unturned. Each chapter is thoughtfully designed to build on the previous one, creating a coherent and thorough learning experience. You'll delve into key subjects such as Julia's type system, multiple dispatch, performance optimization, metaprogramming, and language interoperability. With a focus on writing efficient, elegant, and robust code, this guide offers rich, practical examples, exercises, and case studies to immediately apply your newfound knowledge and observe its impact in practical applications. Ideal for those involved in scientific research, high-performance computing, or anyone fascinated by the expanding capabilities of Julia, Advanced Julia Programming: Comprehensive Techniques and Best Practices is your gateway to mastering this dynamic language. Begin your journey to becoming an expert in Julia and explore the limitless possibilities of high-performance programming. |
| mastering julia 1.0: Essential Pre-University Mathematics for Sciences Julia Riley, Mark Warner, 2021-01-14 Isaac is a Department for Education project at the University of Cambridge that develops understanding and confidence through problem solving in the physical sciences, by combining accessible and concise print resources with a state of the art online study tool. This book is a co-publication between Periphyseos Press/Isaac and Cambridge University Press. ESSENTIAL PRE-UNIVERSITY MATHEMATICS FOR SCIENCES helps you master mathematics for final-year school courses and entry-level university and the maths needed for physics, chemistry and other sciences. Chapters 1-6 cover essential techniques in mathematics for sciences, offering both core practice and more advanced problems. Chapter 7 covers mathematical approaches to scientific problems, including population, money, nuclear chain reactions and random walks in gases and galaxies-each illustrating the power of mathematics. All problems can be answered on the Isaac online platform. Registration is free and gives both students and teachers personalised support through a sophisticated online marking system for all problems. |
| mastering julia 1.0: The Parisian Gentleman Hugo Jacomet, 2015 Home of haute couture and the world's leading fashion houses, Paris and its inhabitants represent sophistication and refinement to the rest of the world. In the city's elegant neighborhoods, debonair Parisian men continue to participate in a centuries-long tradition of sartorial craftsmanship and quality. The Parisian Gentleman is like a dream shopping excursion to the leading men's style-makers, from hidden ateliers and little-known studios to internationally renowned labels such as shirtmakers Charvet, shoemakers Berluti, and the recently revived trunk makers Moynat. The stories behind each house, and the creative minds and artisans who give each brand its unique identity, bring the clothes alive, capturing an unceasing dedication to quality in an era overrun with new, mass-produced trends. Author Hugo Jacomet's portraits of these often-inaccessible marques (or brands) are intimate and illuminating, thanks to his personal connections to many of the leading figures associated with each. His text is accompanied by beautifully shot photographs of the designers, studios, garments, and locations, the majority of which were taken exclusively for this book. |
| mastering julia 1.0: Functional Programming in Java Venkat Subramaniam, 2014 Get ready to program in a whole new way. Functional Programming in Java will help you quickly get on top of the new, essential Java 8 language features and the functional style that will change and improve your code. This short, targeted book will help you make the paradigm shift from the old imperative way to a less error-prone, more elegant, and concise coding style that's also a breeze to parallelize. You'll explore the syntax and semantics of lambda expressions, method and constructor references, and functional interfaces. You'll design and write applications better using the new standards in Java 8 and the JDK. |
| mastering julia 1.0: Julia for Data Science Zacharias Voulgaris, 2016 After covering the importance of Julia to the data science community and several essential data science principles, we start with the basics including how to install Julia and its powerful libraries. Many examples are provided as we illustrate how to leverage each Julia command, dataset, and function. Specialized script packages are introduced and described. Hands-on problems representative of those commonly encountered throughout the data science pipeline are provided, and we guide you in the use of Julia in solving them using published datasets. Many of these scenarios make use of existing packages and built-in functions, as we cover: An overview of the data science pipeline along with an example illustrating the key points, implemented in Julia Options for Julia IDEs Programming structures and functions Engineering tasks, such as importing, cleaning, formatting and storing data, as well as performing data preprocessing Data visualization and some simple yet powerful statistics for data exploration purposes Dimensionality reduction and feature evaluation Machine learning methods, ranging from unsupervised (different types of clustering) to supervised ones (decision trees, random forests, basic neural networks, regression trees, and Extreme Learning Machines) Graph analysis including pinpointing the connections among the various entities and how they can be mined for useful insights. Each chapter concludes with a series of questions and exercises to reinforce what you learned. The last chapter of the book will guide you in creating a data science application from scratch using Julia. |
| mastering julia 1.0: HT THINK LIKE A COMPUTER SCIEN Jeffrey Elkner, Allen B. Downey, Chris Meyers, 2016-10-04 The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer. |
| mastering julia 1.0: Mastering R for Quantitative Finance Edina Berlinger, Ferenc Illés, Milán Badics, Ádám Banai, Gergely Daróczi, Barbara Dömötör, Gergely Gabler, Dániel Havran, Péter Juhász, István Margitai, Balázs Márkus, Péter Medvegyev, Julia Molnár, Balázs Árpád Szűcs, Ágnes Tuza, Tamás Vadász, Kata Váradi, Ágnes Vidovics-Dancs, 2015-03-10 This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R. |
| mastering julia 1.0: C++ Machine Learning Phil Culliton, 2017-12-29 Get introduced to the concepts of Machine Learning and build efficient data models in C++About This Book* Get introduced to the concepts of Machine Learning and see how you can implement them in C++, and build efficient data models for training data using popular libraries such as mlpack and Shark* A detailed guide packed with real-life examples to help you build a solid understanding of Machine Learning.Who This Book Is ForThe target audience is C++ developers who want to get into machine learning, or knowledgeable ML programmers who don't know C++ well but want to use it, and libraries written in it, in their work. The reader should be conversant with at least one programming language, and have some familiarity with strongly-typed languages and vectors/matrices.What you will learn* Model relationships in your data using supervised learning* Uncover insights using clustering and t-SNE* Use ensemble and stack to create more powerful models* Use cuda-convnet and deep learning to solve image recognition problems* Build an end-to-end pipeline that turns what you learn into practical, ready-to-use software* Solve big data problems using Hadoop and Google's MR4CIn DetailMachine Learning tasks are CPU time-consuming. C++ outperforms any other programming language by allowing access to programming constructs to optimize CPU-based number crunching, precision, and memory management normally abstracted away in higher-level languages.This book aims to address the challenges associated with C++ machine learning by introducing you to several useful libraries (mlpack, Shogun, and so on); you'll producing a library of your own code along the way that should make common tasks more straightforward.We begin with a review of the basic concepts you will need to know or brush up on before going further, including math and an intro to the C++ style we'll be using throughout the book. We then deal with the fundamentals of ML-how to handle input, the basic algorithms, and sample cases where the basic algorithms succeed or fail. This is followed by more advanced topics such as complex algorithms, regularization, optimization, and visualizing and understanding data, referring back to earlier work consistently so that you can see the mountains move. We'll then touch upon topics of current interest: computer vision (including sections on CUDA and deep learning), natural language processing, and handling very large datasets.The journey ends with a coda: we go back through the original sample cases, applying what we've learned along the way to rectify the issues we ran into initially. |
| mastering julia 1.0: The Flavor of France in Recipes and Pictures Narcissa G. Chamberlain, 2012-07-01 |
| mastering julia 1.0: Introduction to Julia Programming Sandeep Nagar, 2017-05-05 Julia walks like Python and runs like C. This phrase explains why Julia is fast growing as the most favoured option for data analytics and numerical computation. Julia is the fastest modern open-source language for data science, machine learning and scientific computing. Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS or Stata combined with the speed, capacity and performance of C, C++ or Java.Present books is both for beginners and experienced users. While experienced users can use this as a reference, new users can learn the fine details of julia program's composition. CHAPETRS: 1. Introduction, 2. Object Oriented programming, 3. Basic maths with Julia, 4. Complex Numbers, 5. Rational and Irrational numbers, 6. Mathematical Functions, 7.Arrays, 8. Arrays for matrix operations, 9. String,s 10. Functions, 11. Control Flow, 12. Input Output, 13. |
| mastering julia 1.0: Mastering OSF/Motif Widgets Donald L. McMinds, 1993 |
| mastering julia 1.0: Julia 1.0 Programming Ivo Balbaert, 2018-09-24 Enter the exciting world of Julia, a high-performance language for technical computing Key FeaturesLeverage Julia's high speed and efficiency for your applicationsWork with Julia in a multi-core, distributed, and networked environmentApply Julia to tackle problems concurrently and in a distributed environmentBook Description The release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work. In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications. What you will learnSet up your Julia environment to achieve high productivityCreate your own types to extend the built-in type systemVisualize your data in Julia with plotting packagesExplore the use of built-in macros for testing and debugging, among other usesApply Julia to tackle problems concurrentlyIntegrate Julia with other languages such as C, Python, and MATLABWho this book is for Julia 1.0 Programming is for you if you are a statistician or data scientist who wants a crash course in the Julia programming language while building big data applications. A basic knowledge of mathematics is needed to understand the various methods that are used or created during the course of the book to exploit the capabilities that Julia is designed with. |
Sign in - MyLab & Mastering | Pearson
Pearson Enterprise Learning Environment for online courses, simulations, and IT skills. Sign in or enroll with course ID and access code.
Masteringand Modified Mastering Features - Pearson
Mastering opens to the course last opened. • Non-LMS-integrated courses: Pearsonmylabandmastering.com for all Mastering disciplines and select course to open. • LMS …
Modified Mastering - Pearson
Modified Mastering Navigation Tips To learn more about Modified Mastering™, please contact your Pearson representative. Copyright © 2020 Pearson Education, Inc. or its affiliate(s). All …
Controlling cheating in online courses final - MyLab
How do Mastering assignment settings help make cheating more difficult? In many Mastering items, the values of the variables can be randomized, so that students must know how the …
INTRODUCTION/TRAINING AND SUPPORT - MyLab
The top right corner of the MyLab/Mastering Courses page provides links to: • Account - Enables you to manage your Pearson account by editing your personal information. • Help & Support - …
Move to Modified Mastering - Pearson
Starting today, you can begin by going to the new MyLab and Mastering courses page at www.PearsonMyLabandMastering.com and accessing your current Mastering course(s). You …
D2L MyLab and Mastering Kiosk Configuration Guide - Pearson
This document describes the configuration for enabling the Pearson MyLab and Mastering solution within the Brightspace (formerly known as Desire2Learn or D2L) Learning …
Version 3.1 Administrator Guide - MyLab & Mastering
Pearson's MyLab & Mastering online learning products deliver customizable content and highly personalized study paths, responsive learning tools, and real-time evaluation and diagnostics. …
Instructor Quick Start Guide - MyLab & Mastering | Pearson
MyLab | Nursing consists of two course platforms – MyLab Mastering New Design XL forms offer similar functionality and design, there are some differences. When using this guide, make sure …
Version 3.2 Administrator Guide - MyLab & Mastering | Pearson
Pearson's MyLab & Mastering online learning products deliver customizable content and highly personalized study paths, responsive learning tools, and real-time evaluation and diagnostics. …
Sign in - MyLab & Mastering | Pearson
Pearson Enterprise Learning Environment for online courses, simulations, and IT skills. Sign in or enroll with course ID and access code.
Masteringand Modified Mastering Features - Pearson
Mastering opens to the course last opened. • Non-LMS-integrated courses: Pearsonmylabandmastering.com for all Mastering disciplines and select course to open. • LMS …
Modified Mastering - Pearson
Modified Mastering Navigation Tips To learn more about Modified Mastering™, please contact your Pearson representative. Copyright © 2020 Pearson Education, Inc. or its affiliate(s). All …
Controlling cheating in online courses final - MyLab & Mastering
How do Mastering assignment settings help make cheating more difficult? In many Mastering items, the values of the variables can be randomized, so that students must know how the …
INTRODUCTION/TRAINING AND SUPPORT - MyLab
The top right corner of the MyLab/Mastering Courses page provides links to: • Account - Enables you to manage your Pearson account by editing your personal information. • Help & Support - …
Move to Modified Mastering - Pearson
Starting today, you can begin by going to the new MyLab and Mastering courses page at www.PearsonMyLabandMastering.com and accessing your current Mastering course(s). You …
D2L MyLab and Mastering Kiosk Configuration Guide - Pearson
This document describes the configuration for enabling the Pearson MyLab and Mastering solution within the Brightspace (formerly known as Desire2Learn or D2L) Learning …
Version 3.1 Administrator Guide - MyLab & Mastering
Pearson's MyLab & Mastering online learning products deliver customizable content and highly personalized study paths, responsive learning tools, and real-time evaluation and diagnostics. …
Instructor Quick Start Guide - MyLab & Mastering | Pearson
MyLab | Nursing consists of two course platforms – MyLab Mastering New Design XL forms offer similar functionality and design, there are some differences. When using this guide, make sure …
Version 3.2 Administrator Guide - MyLab & Mastering | Pearson
Pearson's MyLab & Mastering online learning products deliver customizable content and highly personalized study paths, responsive learning tools, and real-time evaluation and diagnostics. …
