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| getting started with julia: Getting Started with Julia Ivo Balbaert, 2015-02-26 This book is for you if you are a data scientist or working on any technical or scientific computation projects. The book assumes you have a basic working knowledge of high-level dynamic languages such as MATLAB, R, Python, or Ruby. |
| getting started with julia: 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. |
| getting started with julia: Beginning Julia Programming Sandeep Nagar, 2017-11-25 Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how 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. You’ll learn the OOP principles required to get you started, then how to do basic mathematics with Julia. Other core functionality of Julia that you’ll cover, includes working with complex numbers, rational and irrational numbers, rings, and fields. Beginning Julia Programming takes you beyond these basics to harness Julia’s powerful features for mathematical functions in Julia, arrays for matrix operations, plotting, and more. Along the way, you also learn how to manage strings, write functions, work with control flows, and carry out I/O to implement and leverage the mathematics needed for your data scienceand analysis projects. Julia walks like Python and runs like C. This phrase explains why Julia is quickly growing as the most favored option for data analytics and numerical computation. After reading and using this book, you'll have the essential knowledge and skills to build your first Julia-based application. What You'll Learn Obtain core skills in Julia Apply Julia in engineering and science applications Work with mathematical functions in Julia Use arrays, strings, functions, control flow, and I/O in Julia Carry out plotting and display basic graphics Who This Book Is For Those who are new to Julia; experienced users may also find this helpful as a reference. |
| getting started with julia: 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 |
| getting started with julia: 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 |
| getting started with julia: Julia Quick Syntax Reference Antonello Lobianco, 2019-11-11 This quick Julia programming language guide is a condensed code and syntax reference to the Julia 1.x programming language, updated with the latest features of the Julia APIs, libraries, and packages. It presents the essential Julia syntax in a well-organized format that can be used as a handy reference. This book provides an introduction that reveals basic Julia structures and syntax; discusses data types, control flow, functions, input/output, exceptions, metaprogramming, performance, and more. Additionally, you'll learn to interface Julia with other programming languages such as R for statistics or Python. You will learn how to use Julia packages for data analysis, numerical optimization and symbolic computation, and how to disseminate your results in dynamic documents or interactive web pages. In this book, the focus is on providing important information as quickly as possible. It is packed with useful information and is a must-have for any Julia programmer. What You Will Learn Set up the software needed to run Julia and your first Hello World example Work with types and the different containers that Julia makes available for rapid application development Use vectorized, classical loop-based code, logical operators, and blocks Explore Julia functions by looking at arguments, return values, polymorphism, parameters, anonymous functions, and broadcasts Build custom structures in Julia Interface Julia with other languages such as C/C++, Python, and R Program a richer API, modifying the code before it is executed using expressions, symbols, macros, quote blocks, and more Maximize your code’s performance Who This Book Is For Experienced programmers new to Julia, as well as existing Julia coders new tothe now stable Julia version 1.0 release. |
| getting started with julia: Data Science with Julia Paul D. McNicholas, Peter Tait, 2019-01-02 This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist.- Professor Charles Bouveyron, INRIA Chair in Data Science, Université Côte d’Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Discusses several important topics in data science including supervised and unsupervised learning. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. Presents how to optimize Julia code for performance. Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). The advantages of Julia for data science cannot be understated. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist. Professor Charles Bouveyron INRIA Chair in Data Science Université Côte d’Azur, Nice, France |
| getting started with julia: Introduction to Applied Linear Algebra Stephen Boyd, Lieven Vandenberghe, 2018-06-07 A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples. |
| getting started with julia: Numerical Methods for Scientific Computing Kyle Novak, 2022-03-13 A comprehensive guide to the theory, intuition, and application of numerical methods in linear algebra, analysis, and differential equations. With extensive commentary and code for three essential scientific computing languages: Julia, Python, and Matlab. |
| getting started with julia: 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. |
| getting started with julia: 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. |
| getting started with julia: Simply Living Well Julia Watkins, 2020 Easy recipes, DIY projects, and other ideas for living a beautiful and low-waste life, from the expert behind @simply.living.well on Instagram. |
| getting started with julia: The Three Little Fish and the Big Bad Shark Ken Geist, 2016-06-26 A hilarious under-the-sea retelling of The Three Little Pigs! Little fish, little fish, let me come in.Not by the skin of my finny fin fin!Then I'll munch, and I'll crunch, and I'll smash your house in!Mama tells her three little fish that it's time to make their own homes. Jim builds his house of seaweed, but the big bad shark munches it up. Tim builds his house of sand, but the shark crunches it up. It's smart Kim who sets up house in an old sunken ship!Children will delight in this silly whale of a tale with funny, eye-popping illustrations!Safe for all ages. |
| getting started with julia: Get Started with Gouache Emma Block, 2020-07-07 A modern, easy-to-use, and authoritative guide to painting with gouache, including the basics on this exciting and centuries-old medium, techniques for all skill levels, and practice projects from an experienced author and illustrator. This charming and contemporary step-by-step guide to gouache (pronounced gwash) is perfect for creative people who have dreamed of painting inspiring subjects from everyday life. Gouache is a water-based paint similar to watercolor that has the opacity and layerability of acrylic paints. It creates wonderful washes, allows for layering and texture, and dries quickly with a unique matte finish. Illustrator Emma Block presents everything you need to know about this whimsical and fun medium, including expert guidance on tools and materials and techniques that will make it easy to use. Thirty lessons cover subjects from simple, such as your morning coffee cup and bright lemons, to advanced, such as fluffy animals and portraits of your friends and family. All of this is accompanied by her workshop-honed instructions and step-by-step illustrations, which will help you build the skills and confidence to finish beautiful pieces of your own. |
| getting started with julia: Dust & Grooves Eilon Paz, 2015-09-15 A photographic look into the world of vinyl record collectors—including Questlove—in the most intimate of environments—their record rooms. Compelling photographic essays from photographer Eilon Paz are paired with in-depth and insightful interviews to illustrate what motivates these collectors to keep digging for more records. The reader gets an up close and personal look at a variety of well-known vinyl champions, including Gilles Peterson and King Britt, as well as a glimpse into the collections of known and unknown DJs, producers, record dealers, and everyday enthusiasts. Driven by his love for vinyl records, Paz takes us on a five-year journey unearthing the very soul of the vinyl community. |
| getting started with julia: The Scout Mindset Julia Galef, 2021-04-13 ...an engaging and enlightening account from which we all can benefit.—The Wall Street Journal A better way to combat knee-jerk biases and make smarter decisions, from Julia Galef, the acclaimed expert on rational decision-making. When it comes to what we believe, humans see what they want to see. In other words, we have what Julia Galef calls a soldier mindset. From tribalism and wishful thinking, to rationalizing in our personal lives and everything in between, we are driven to defend the ideas we most want to believe—and shoot down those we don't. But if we want to get things right more often, argues Galef, we should train ourselves to have a scout mindset. Unlike the soldier, a scout's goal isn't to defend one side over the other. It's to go out, survey the territory, and come back with as accurate a map as possible. Regardless of what they hope to be the case, above all, the scout wants to know what's actually true. In The Scout Mindset, Galef shows that what makes scouts better at getting things right isn't that they're smarter or more knowledgeable than everyone else. It's a handful of emotional skills, habits, and ways of looking at the world—which anyone can learn. With fascinating examples ranging from how to survive being stranded in the middle of the ocean, to how Jeff Bezos avoids overconfidence, to how superforecasters outperform CIA operatives, to Reddit threads and modern partisan politics, Galef explores why our brains deceive us and what we can do to change the way we think. |
| getting started with julia: The Farmer's Office Julia Shanks, 2016-09-01 A practical, how-to guide for farmers who want to achieve and maintain financial sustainability in their businesses When you decided to become a farmer, you also became an entrepreneur and business person. In order to be ecologically and financially sustainable, you must understand the basics of accounting and bookkeeping, and learn how to manage a growing business. Author Julia Shanks distills years of teaching and business consulting with farmers into this comprehensive, accessible guide. She covers all aspects of launching, running and growing a successful farm business through effective bookkeeping and business management, providing tools to make managerial decisions, apply for a loan or other financing, and offering general business and strategy advice for growing a business. Whether you've been farming for many years or just getting started, The Farmer's Office gives you the tools needed to think like an entrepreneur and thoughtfully manage your business for success. |
| getting started with julia: Bayesian Methods for Hackers Cameron Davidson-Pilon, 2015-09-30 Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify. |
| getting started with julia: 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 |
| getting started with julia: First Year Teacher's Survival Guide Julia G. Thompson, 2012-06-14 The best-selling First Year Teacher's Survival Kit gives new teachers a wide variety of tested strategies, activities, and tools for creating a positive and dynamic learning environment while meeting the challenges of each school day. Packed with valuable tips, the book helps new teachers with everything from becoming effective team players and connecting with students to handling behavior problems and working within diverse classrooms. The new edition is fully revised and updated to cover changes in the K-12 classroom over the past five years. Updates to the second edition include: • New ways teachers can meet the professional development requirements of the No Child Left Behind Act • Entirely new section on helping struggling readers, to address the declining literacy rate among today’s students • Expanded coverage of helpful technology solutions for the classroom • Expanded information on teaching English Language Learners • Greater coverage of the issues/challenges facing elementary teachers • More emphasis on how to reach and teach students of poverty • Updated study techniques that have proven successful with at-risk students • Tips on working effectively within a non-traditional school year schedule • The latest strategies for using graphic organizers • More emphasis on setting goals to help students to succeed • More information on intervening with students who are capable but choose not to work • Updated information on teachers’ rights and responsibilities regarding discipline issues • Fully revised Resources appendix including the latest educational Web sites and software |
| getting started with julia: 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. |
| getting started with julia: Words on Bathroom Walls Julia Walton, 2018-12-31 Now a Major Motion Picture starring Charlie Plummer, AnnaSophia Robb, and Taylor Russell! Fans of More Happy Than Not and The Perks of Being a Wallflower will cheer for Adam in this uplifting and surprisingly funny story of a boy living with schizophrenia. When you can't trust your mind, trust your heart. Adam is a pretty regular teen, except he's navigating high school life while living with paranoid schizophrenia. His hallucinations include a cast of characters that range from the good (beautiful Rebecca) to the bad (angry Mob Boss) to the just plain weird (polite naked guy). An experimental drug promises to help him hide his illness from the world. When Adam meets Maya, a fiercely intelligent girl, he desperately wants to be the normal, great guy that she thinks he is. But as the miracle drug begins to fail, how long can he keep this secret from the girl of his dreams? Echoing the premise and structure of Flowers for Algernon, this [is a] frank and inspiring novel. --Publishers Weekly, starred review Don't miss Just Our Luck, another stunning book by Julia Walton. Coming in 2020! |
| getting started with julia: 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. |
| getting started with julia: As Always, Julia Julia Child, 2012 This dishy and delightful, never-before-published correspondence between America's queen of food, Julia Child, and her mentor Avis DeVoto, shows not only the blossoming of a lifelong friendship, but also an America on the verge of transformation. |
| getting started with julia: The Little Book of Julia Algorithms Ahan Sengupta, William Lau, 2021 |
| getting started with julia: Julia High Performance Avik Sengupta, 2019-06-11 |
| getting started with julia: Hands-On Computer Vision with Julia Dmitrijs Cudihins, 2018-06-29 Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking. Key Features Build a full-fledged image processing application using JuliaImages Perform basic to advanced image and video stream processing with Julia's APIs Understand and optimize various features of OpenCV with easy examples Book Description Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it's easy to use and lets you write easy-to-compile and efficient machine code. . This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You'll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you'll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease. What you will learn Analyze image metadata and identify critical data using JuliaImages Apply filters and improve image quality and color schemes Extract 2D features for image comparison using JuliaFeatures Cluster and classify images with KNN/SVM machine learning algorithms Recognize text in an image using the Tesseract library Use OpenCV to recognize specific objects or faces in images and videos Build neural network and classify images with MXNet Who this book is for Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively. |
| getting started with julia: The Way to Go Ivo Balbaert, 2012 This book provides the reader with a comprehensive overview of the new open source programming language Go (in its first stable and maintained release Go 1) from Google. The language is devised with Java / C#-like syntax so as to feel familiar to the bulk of programmers today, but Go code is much cleaner and simpler to read, thus increasing the productivity of developers. You will see how Go: simplifies programming with slices, maps, structs and interfaces incorporates functional programming makes error-handling easy and secure simplifies concurrent and parallel programming with goroutines and channels And you will learn how to: make use of Go's excellent standard library program Go the idiomatic way using patterns and best practices in over 225 working examples and 135 exercises This book focuses on the aspects that the reader needs to take part in the coming software revolution using Go. |
| getting started with julia: Migratory Birds Mariana Oliver, 2021 A sensitive, stunning debut on movement, migration, and loss, in the vein of Valeria Luiselli's Sidewalks. |
| getting started with julia: Getting Started with Natural Language Processing Ekaterina Kochmar, 2022-11-15 Hit the ground running with this in-depth introduction to the NLP skills and techniques that allow your computers to speak human. In Getting Started with Natural Language Processing you’ll learn about: Fundamental concepts and algorithms of NLP Useful Python libraries for NLP Building a search algorithm Extracting information from raw text Predicting sentiment of an input text Author profiling Topic labeling Named entity recognition Getting Started with Natural Language Processing is an enjoyable and understandable guide that helps you engineer your first NLP algorithms. Your tutor is Dr. Ekaterina Kochmar, lecturer at the University of Bath, who has helped thousands of students take their first steps with NLP. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. If you’re a beginner to NLP and want to upgrade your applications with functions and features like information extraction, user profiling, and automatic topic labeling, this is the book for you. About the technology From smart speakers to customer service chatbots, apps that understand text and speech are everywhere. Natural language processing, or NLP, is the key to this powerful form of human/computer interaction. And a new generation of tools and techniques make it easier than ever to get started with NLP! About the book Getting Started with Natural Language Processing teaches you how to upgrade user-facing applications with text and speech-based features. From the accessible explanations and hands-on examples in this book you’ll learn how to apply NLP to sentiment analysis, user profiling, and much more. As you go, each new project builds on what you’ve previously learned, introducing new concepts and skills. Handy diagrams and intuitive Python code samples make it easy to get started—even if you have no background in machine learning! What's inside Fundamental concepts and algorithms of NLP Extracting information from raw text Useful Python libraries Topic labeling Building a search algorithm About the reader You’ll need basic Python skills. No experience with NLP required. About the author Ekaterina Kochmar is a lecturer at the Department of Computer Science of the University of Bath, where she is part of the AI research group. Table of Contents 1 Introduction 2 Your first NLP example 3 Introduction to information search 4 Information extraction 5 Author profiling as a machine-learning task 6 Linguistic feature engineering for author profiling 7 Your first sentiment analyzer using sentiment lexicons 8 Sentiment analysis with a data-driven approach 9 Topic analysis 10 Topic modeling 11 Named-entity recognition |
| getting started with julia: The Sum of Trifles Julia Ridley Smith, 2021-11-01 When Julia Ridley Smith’s parents died, they left behind a virtual museum of furniture, books, art, and artifacts. Between the contents of their home, the stock from their North Carolina antiques shop, and the ephemera of two lives lived, Smith faced a monumental task. What would she do with her parents’ possessions? Smith’s wise and moving memoir in essays, The Sum of Trifles, peels back the layers of meaning surrounding specific objects her parents owned, from an eighteenth-century miniature to her father’s prosthetics. A vintage hi-fi provides a view of her often tense relationship with her father, whose love of jazz kindled her own artistic impulse. A Japanese screen embodies her mother’s principles of good taste and good manners, while an antebellum quilt prompts Smith to grapple with her family’s slaveholding legacy. Along the way, she turns to literature that illuminates how her inheritance shaped her notions of identity and purpose. The Sum of Trifles offers up dark humor and raw feeling, mixed with an erudite streak. It’s a curious, thoughtful look at how we live in and with our material culture and how we face our losses as we decide what to keep and what to let go. |
| getting started with julia: Kitchen Garden Revival Nicole Johnsey Burke, 2020-04-14 Elevate your backyard veggie patch into a work of sophisticated and stylish art. Kitchen Garden Revival guides you through every aspect of kitchen gardening, from design to harvesting—with expert advice from author Nicole Johnsey Burke, founder of Rooted Garden, one of the leading US culinary landscape companies, and Gardenary, an online kitchen gardening education and resource company. Participating in the grow-your-own movement is important to both reduce your food miles and control what makes it onto your family’s table. If you’ve hesitated to take part because installing and caring for a traditional vegetable garden doesn’t seem to suit your life or your sense of style, Kitchen Garden Revival is here to show you there’s a better, more beautiful way to grow food. Instead of row after row of cabbage and pepper plants plunked into a patch of dirt in the middle of the yard, kitchen gardens are attractive, highly tailored food gardens consisting of easy-to-maintain raised planting beds laid out in an organized geometric pattern. Offering both four seasons of ornamental interest and plenty of fresh, homegrown fruits, vegetables, and herbs, kitchen gardens are the way to grow your own food in a fashionable, modern, and practical way. Kitchen gardens were once popular features of the European and early American landscape, but they fell out of favor when our agrarian roots were displaced by industrialization. With this accessible and inspirational guide, Nicole aims to return the kitchen garden to its rightful place just outside of every backdoor. Learn the art of kitchen gardening as you discover: What characteristics all kitchen gardens have in common How to design and install gorgeous kitchen garden beds using metal, wood, or stone Why raised beds mean reduced maintenance What crops are best for your kitchen garden A planting, tending, and harvesting plan developed by a pro Season-by-season growing guides It's time to join the Kitchen Garden Revival and start growing your own delicious, organic food. |
| getting started with julia: Mastering Julia Malcolm Sherrington, 2024-01-19 A hands-on, code-based guide to leveraging Julia in a variety of scientific and data-driven scenarios Key Features Augment your basic computing skills with an in-depth introduction to Julia Focus on topic-based approaches to scientific problems and visualisation Build on prior knowledge of programming languages such as Python, R, or C/C++ Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionJulia is a well-constructed programming language which was designed for fast execution speed by using just-in-time LLVM compilation techniques, thus eliminating the classic problem of performing analysis in one language and translating it for performance in a second. This book is a primer on Julia’s approach to a wide variety of topics such as scientific computing, statistics, machine learning, simulation, graphics, and distributed computing. Starting off with a refresher on installing and running Julia on different platforms, you’ll quickly get to grips with the core concepts and delve into a discussion on how to use Julia with various code editors and interactive development environments (IDEs). As you progress, you’ll see how data works through simple statistics and analytics and discover Julia's speed, its real strength, which makes it particularly useful in highly intensive computing tasks. You’ll also and observe how Julia can cooperate with external processes to enhance graphics and data visualization. Finally, you will explore metaprogramming and learn how it adds great power to the language and establish networking and distributed computing with Julia. By the end of this book, you’ll be confident in using Julia as part of your existing skill set.What you will learn Develop simple scripts in Julia using the REPL, code editors, and web-based IDEs Get to grips with Julia’s type system, multiple dispatch, metaprogramming, and macro development Interact with data files, tables, data frames, SQL, and NoSQL databases Delve into statistical analytics, linear programming, and optimization problems Create graphics and visualizations to enhance modeling and simulation in Julia Understand Julia's main approaches to machine learning, Bayesian analysis, and AI Who this book is for This book is not an introduction to computer programming, but a practical guide for developers who want to enhance their basic knowledge of Julia, or those wishing to augment their skill set by adding Julia to their existing roster of programming languages. Familiarity with a scripting language such as Python or R, or a compiled language such as C/C++, C# or Java, is a prerequisite. |
| getting started with julia: The Truth About Julia Anna Schaffner, 2017-01-01 How many versions of the truth can there be? In June 2014, Julia White - a beautiful and intelligent young woman - blows up a coffee shop in central London, killing twenty-four people before turning herself in to the police. Apart from publishing a potentially ironic manifesto, she refuses to explain the reasons for her actions. Clare Hardenberg, an investigative journalist, has been commissioned to write a biography of Julia but at the start of the novel she is on her way to prison herself. What has brought her to this point? |
| getting started with julia: The Upstairs House Julia Fine, 2022-02-22 A Good Morning America Book of the Month Selection * A Popsugar Must-Read Book of the Month * A Buzzfeed Most Anticipated Book of the Year * A The Millions Most Anticipated Book of the Year Provocative.... [An] assured, beautifully written book. --Sarah Lyall, New York Times In this provocative meditation on new motherhood--Shirley Jackson meets The Awakening--a postpartum woman's psychological unraveling becomes intertwined with the ghostly appearance of children's book writer Margaret Wise Brown. There's a madwoman upstairs, and only Megan Weiler can see her. Ravaged and sore from giving birth to her first child, Megan is mostly raising her newborn alone while her husband travels for work. Physically exhausted and mentally drained, she's also wracked with guilt over her unfinished dissertation--a thesis on mid-century children's literature. Enter a new upstairs neighbor: the ghost of quixotic children's book writer Margaret Wise Brown--author of the beloved classic Goodnight Moon--whose existence no one else will acknowledge. It seems Margaret has unfinished business with her former lover, the once-famous socialite and actress Michael Strange, and is determined to draw Megan into the fray. As Michael joins the haunting, Megan finds herself caught in the wake of a supernatural power struggle--and until she can find a way to quiet these spirits, she and her newborn daughter are in terrible danger. Using Megan's postpartum haunting as a powerful metaphor for a woman's fraught relationship with her body and mind, Julia Fine once again delivers an imaginative and barely restrained, careful musing on female desire, loneliness, and hereditary inheritances (Washington Post). |
| getting started with julia: The Julia Language Handbook George Root, 2019-02-02 If you are new to Julia and want a reference that describes how to install and use Julia, this is the book you want. Many of the other Julia books available describe previous versions with examples that no longer work. The Julia Handbook is current as of Julia v1.02 and every example, of which there are dozens, has been tested and they all work.You will learn how to install and use the Julia REPL mode and the Jupyter Notebook mode to create and test your code. Other topics include:Data TypesFunctions and PackagesTuplesData ArraysData FramesData StructuresFlow ControlLoops and IterationInput / Output - formatted printing - writing and reading data filesLine and Scatter PlotsOther Plot TypesRandom NumbersOptimization Using Optim and JuMPThis is the book I wanted to buy when I started learning Julia but I had to write it myself to get all of the detail and up-to-date information I wanted. If you are just learning Julia you will find this to be a useful guide. If you are already using Julia you will find this to be an excellent reference book to remind you of some obscure Julia syntax. |
| getting started with julia: Interactive Visualization and Plotting with Julia Diego Javier Zea, 2022-08-29 Represent and analyze data using Plots to find actionable insights using Julia programming Key FeaturesLearn to use static and interactive plots to explore data with JuliaBecome well versed with the various plotting attributes needed to customize your plotsCreate insightful and appealing plots using data interactions, animations, layouts, and themesBook Description The Julia programming language offers a fresh perspective into the data visualization field. Interactive Visualization and Plotting with Julia begins by introducing the Julia language and the Plots package. The book then gives a quick overview of the Julia plotting ecosystem to help you choose the best library for your task. In particular, you will discover the many ways to create interactive visualizations with its packages. You'll also leverage Pluto notebooks to gain interactivity and use them intensively through this book. You'll find out how to create animations, a handy skill for communication and teaching. Then, the book shows how to solve data analysis problems using DataFrames and various plotting packages based on the grammar of graphics. Furthermore, you'll discover how to create the most common statistical plots for data exploration. Also, you'll learn to visualize geographically distributed data, graphs and networks, and biological data. Lastly, this book will go deeper into plot customizations with Plots, Makie, and Gadfly—focusing on the former—teaching you to create plot themes, arrange multiple plots into a single figure, and build new plot types. By the end of this Julia book, you'll be able to create interactive and publication-quality static plots for data analysis and exploration tasks using Julia. What you will learnCreate interactive plots with Makie, Plots, Jupyter, and PlutoCreate standard statistical plots and visualize clustering resultsPlot geographically distributed and biological dataVisualize graphs and networks using GraphRecipes and GraphPlotsFind out how to draw and animate objects with Javis, Plots, and MakieDefine plot themes to reuse plot visual aspect customizationsArrange plots using Plots, Makie, and Gadfly layout systemsDefine new plot types and determine how Plots and Makie show objectsWho this book is for Data analysts looking to explore Julia's data visualization capabilities will find this book helpful, along with scientists and academics who want to generate and communicate knowledge and improve their teaching material. This data visualization book will also interest Julia programmers willing to delve into the language plotting ecosystem and improve their visualization skills. Basic programming knowledge is assumed — but the book will introduce you to Julia's important features. Familiarity with mathematical and statistical concepts will help you make the most of some of the chapters. |
| getting started with julia: Julia Programming Projects Adrian Salceanu, 2018-12-26 A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key FeaturesWork with powerful open-source libraries for data wrangling, analysis, and visualizationDevelop full-featured, full-stack web applications Learn to perform supervised and unsupervised machine learning and time series analysis with JuliaBook Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learnLeverage Julia's strengths, its top packages, and main IDE optionsAnalyze and manipulate datasets using Julia and DataFramesWrite complex code while building real-life Julia applicationsDevelop and run a web app using Julia and the HTTP packageBuild a recommender system using supervised machine learning Perform exploratory data analysis Apply unsupervised machine learning algorithmsPerform time series data analysis, visualization, and forecastingWho this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed. |
| getting started with julia: New Mexico Bouldering Owen Summerscales, 2016-03-10 The Land of Enchantment is known for its scenic natural beauty and plentiful rock climbing, with its rich geology and excellent climate. This book is the first guide to bouldering in the state and compiles over 1000 problems in central and northern NM, with 40 maps and 240 topographic photos. Areas covered include: Socorro Box Canyon, Albuquerque Sandia Mountains, Ponderosa, the Ortegas and Roy. |
| getting started with julia: Think Julia Ben Lauwens, Allen B. Downey, 2019-04-05 If you’re just learning how to program, Julia is an excellent JIT-compiled, dynamically typed language with a clean syntax. This hands-on guide uses Julia 1.0 to walk you through programming one step at a time, beginning with basic programming concepts before moving on to more advanced capabilities, such as creating new types and multiple dispatch. Designed from the beginning for high performance, Julia is a general-purpose language ideal for not only numerical analysis and computational science but also web programming and scripting. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Julia is perfect for students at the high school or college level as well as self-learners and professionals who need to learn programming basics. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand types, methods, and multiple dispatch Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design and data structures through case studies |
to get VS. getting - English Language Learners Stack Exchange
Dec 31, 2014 · When I have to catch a train, I'm always worried that I'll miss it. So, I like getting/ to get to the station in plenty of time. In grammar in use book, the bold part has been considered as …
To get vs in getting - English Language Learners Stack Exchange
Which one is correct- He did not succeed to get the job though he tried his level best. He did not succeed in getting the job though he tried his level best. Book says second one is correct.
"to getting" vs. "to get" - English Language Learners Stack Exchange
The "to getting" examples are transitive. Since they are in a gerundive form, it's hard to see this, so I'll create a transitive sentence from them to make the point. The Essential Guide to Getting Your …
"is getting" vs "will get" - English Language Learners Stack Exchange
Alex is getting married next month. Alex will get married next month. Seems that the first one is expressed in present continues, and the second on in future tense.
grammar - Being vs Getting difference - English Language Learners …
Apr 10, 2022 · Getting is the present participle of get. So the only difference is the different definitions of be and get. To be is to exist or to happen. To get is to receive something. So the …
Being vs Getting - English Language Learners Stack Exchange
Jul 17, 2020 · Being =/= getting. However, that quote means that the person undergoing eye surgery may expect to have perfect vision as a best case outcome. DISCLAIMER: I may be wrong. …
Meaning of "be getting - English Language Learners Stack Exchange
Nov 30, 2020 · We are getting prepared. We are doing something now and as a result at some future time we will be ready. We are getting married. We are planning to do this at some future …
Difference between "get in touch with" and "contact"
Existing comments have clarified that it should be 'getting in touch with' or 'contacting'. 'Contacting with' doesn't work, though 'getting in contact with' is possible - I just wouldn't use it in either of …
What does "get personal" mean in this article?
Does it mean "have personal relationships", "getting to know them more", or something like that? "Get personal. Lauren Mauro, the director of both consumer PR and influencer relations at Dell, …
What's a natural way to say "I am getting familiar with something"
Jun 25, 2019 · "Acquainted" can be used for things, but "getting acquainted" is more commonly used to describe people mutually getting to know one another. I would therefore use: I am …
to get VS. getting - English Language Learners Stack Exchange
Dec 31, 2014 · When I have to catch a train, I'm always worried that I'll miss it. So, I like getting/ to get to the station in plenty of time. In grammar in use book, the bold part has been considered …
To get vs in getting - English Language Learners Stack Exchange
Which one is correct- He did not succeed to get the job though he tried his level best. He did not succeed in getting the job though he tried his level best. Book says second one is correct.
"to getting" vs. "to get" - English Language Learners Stack Exchange
The "to getting" examples are transitive. Since they are in a gerundive form, it's hard to see this, so I'll create a transitive sentence from them to make the point. The Essential Guide to Getting …
"is getting" vs "will get" - English Language Learners Stack Exchange
Alex is getting married next month. Alex will get married next month. Seems that the first one is expressed in present continues, and the second on in future tense.
grammar - Being vs Getting difference - English Language …
Apr 10, 2022 · Getting is the present participle of get. So the only difference is the different definitions of be and get. To be is to exist or to happen. To get is to receive something. So the …
Being vs Getting - English Language Learners Stack Exchange
Jul 17, 2020 · Being =/= getting. However, that quote means that the person undergoing eye surgery may expect to have perfect vision as a best case outcome. DISCLAIMER: I may be …
Meaning of "be getting - English Language Learners Stack Exchange
Nov 30, 2020 · We are getting prepared. We are doing something now and as a result at some future time we will be ready. We are getting married. We are planning to do this at some future …
Difference between "get in touch with" and "contact"
Existing comments have clarified that it should be 'getting in touch with' or 'contacting'. 'Contacting with' doesn't work, though 'getting in contact with' is possible - I just wouldn't use it in either of …
What does "get personal" mean in this article?
Does it mean "have personal relationships", "getting to know them more", or something like that? "Get personal. Lauren Mauro, the director of both consumer PR and influencer relations at …
What's a natural way to say "I am getting familiar with something"
Jun 25, 2019 · "Acquainted" can be used for things, but "getting acquainted" is more commonly used to describe people mutually getting to know one another. I would therefore use: I am …
