Download or read book Think Julia written by Ben Lauwens and published by "O'Reilly Media, Inc.". This book was released on 2019-04-05 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book The Notebook Girls written by Julia Baskin and published by Grand Central Publishing. This book was released on 2008-11-15 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: We're just a group of normal girls with normal lives. Our notebook is meant to make you laugh—​and make you remember. Everyone likes to think they started the notebook. Sophie claims she stole the idea from two girls in her math class. Courtney still has a death grip on the theory that the notebook was her invention. Lindsey doesn't really care; she's just along for the ride. And Julia never knows what's going on anyway. What we do know is that we started the notebook in freshman year at Stuyvesant High School as a way to keep in contact when our conflicting schedules denied us one another's company. It allowed us to express ourselves and our views of the world in a tone of complete sarcasm, obscenity, and blind honesty. We've spent a significant portion of our adolescence trying to figure out who we are. The notebook is the closest we've come.

Download or read book Statistics with Julia written by Yoni Nazarathy and published by Springer Nature. This book was released on 2021-09-04 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The Julia Rothman Collection written by Julia Rothman and published by Storey Publishing, LLC. This book was released on 2016-11-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handsome box set provides hours of enlightening entertainment for those curious about farm life, the natural world, and food. Best-selling author and illustrator Julia Rothman presents Farm Anatomy, Nature Anatomy, and Food Anatomy in a specially designed slipcase with 10 framable prints. Rothman’s popular line drawings offer a whimsical and educational guide to life on a farm, nature’s hidden wonders, and delectable tidbits from kitchens and pantries around the globe.

Download or read book Algorithms for Decision Making written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2022-08-16 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems—used in applications that range from aircraft collision avoidance to breast cancer screening—must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act through interaction with the environment; state uncertainty, in which we do not know the current state of the environment due to imperfect perceptual information; and decision contexts involving multiple agents. The book focuses primarily on planning and reinforcement learning, although some of the techniques presented draw on elements of supervised learning and optimization. Algorithms are implemented in the Julia programming language. Figures, examples, and exercises convey the intuition behind the various approaches presented.

Download or read book Interactive Visualization and Plotting with Julia written by Diego Javier Zea and published by Packt Publishing Ltd. This book was released on 2022-08-29 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Farm Anatomy written by Julia Rothman and published by Storey Publishing. This book was released on 2011-10-01 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the difference between a farrow and a barrow, and what distinguishes a weanling from a yearling. Country and city mice alike will delight in Julia Rothman’s charming illustrated guide to the curious parts and pieces of rural living. Dissecting everything from the shapes of squash varieties to how a barn is constructed and what makes up a beehive to crop rotation patterns, Rothman gives a richly entertaining tour of the quirky details of country life.

Download or read book Nature Anatomy written by Julia Rothman and published by Storey Publishing, LLC. This book was released on 2015-10-09 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: See the world in a whole new way! Acclaimed illustrator Julia Rothman combines art and science in this exciting and educational guide to the structure, function, and personality of the natural world. Explore the anatomy of a jellyfish, the inside of a volcano, monarch butterfly migration, how sunsets work, and much more. Rothman’s whimsical illustrations are paired with interactive activities that encourage curiosity and inspire you to look more closely at the world all around you. Nature Anatomy is the second book in Rothman's Anatomy series – you'll love Nature Anatomy Notebook, Ocean Anatomy, Food Anatomy, and Farm Anatomy, too!

Download or read book Learning Julia written by Anshul Joshi and published by Packt Publishing Ltd. This book was released on 2017-11-24 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Breast Cancer written by Julia Chiappetta and published by . This book was released on 2006-01-01 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Ocean Anatomy written by Julia Rothman and published by Storey Publishing, LLC. This book was released on 2020-04-28 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Julia Rothman’s best-selling illustrated Anatomy series takes a deep dive into the wonders of the sea with Ocean Anatomy. Follow Rothman’s inquisitive mind and perceptive eye along shorelines, across the open ocean, and below the waves for an artistic exploration of the watery universe. Through her drawings, discover how the world’s oceans formed, why the sea is salty, and the forces behind oceanic phenomena such as rogue waves. Colorful anatomical profiles of sea creatures from crustacean to cetacean, surveys of seafaring vessels and lighthouses, and the impact of plastic and warming water temperatures are just part of this compendium of curiosities that will entertain and educate readers of all ages. Also available in this series: Nature Anatomy, Farm Anatomy, Food Anatomy, and Nature Anatomy Notebook

Download or read book Nature Anatomy Notebook written by Julia Rothman and published by Storey Publishing, LLC. This book was released on 2019-04-30 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adults and children are irresistibly drawn to Julia Rothman’s best-selling illustrated guide to the natural world, Nature Anatomy, with its colorful drawings that awaken curiosity — and invite imitation. With this companion volume, Rothman leads fans deeper into nature observation with her specially designed record pages for tracking daily nature sightings throughout the seasons. Her step-by-step technique tutorials for drawing a flower, a dragonfly, a robin, and much more, along with blank sketchbook pages, will inspire nature lovers and art enthusiasts of all ages to take up their own colored pencils or favorite pens and create their own unique Nature Anatomy Notebook. Also available in Julia Rothman's Anatomy series: Ocean Anatomy, Farm Anatomy, and Food Anatomy.

Download or read book Hands On Julia Programming written by Sambit Kumar Dash and published by BPB Publications. This book was released on 2021-10-21 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build production-ready machine learning and NLP systems using functional programming, development platforms, and cloud deployment. KEY FEATURES ● In-depth explanation and code samples highlighting the features of the Julia language. ● Extensive coverage of the Julia development ecosystem, package management, DevOps environment integration, and performance management tools. ● Exposure to the most important Julia packages that aid in Data and Text Analytics and Deep Learning. DESCRIPTION The Julia Programming language enables data scientists and programmers to create prototypes without sacrificing performance. Nonetheless, skeptics question its readiness for production deployments as a new platform with a 1.0 release in 2018. This book removes these doubts and offers a comprehensive glimpse at the language's use throughout developing and deploying production-ready applications. The first part of the book teaches experienced programmers and scientists about the Julia language features in great detail. The second part consists of gaining hands-on experience with the development environment, debugging, programming guidelines, package management, and cloud deployment strategies. In the final section, readers are introduced to a variety of third-party packages available in the Julia ecosystem for Data Processing, Text Analytics, and developing Deep Learning models. This book provides an extensive overview of the programming language and broadens understanding of the Julia ecosystem. As a result, it assists programmers, scientists, and information architects in selecting Julia for their next production deployments. WHAT YOU WILL LEARN ● Get to know the complete fundamentals of Julia programming. ● Explore Julia development frameworks and how to work with them. ● Dig deeper into the concepts and applications of functional programming. ● Uncover the Julia infrastructure for development, testing, and deployment. ● Learn to practice Julia libraries and the Julia package ecosystem. ● Processing Data, Deep Learning, and Natural Language Processing with Julia. WHO THIS BOOK IS FOR This book is for Data Scientists and application developers who want to learn about Julia application development. No prior Julia knowledge is required but knowing the basics of programming helps understand the objectives of this book. TABLE OF CONTENTS 1. Getting Started 2. Data Types 3. Conditions, Control Flow, and Iterations 4. Functions and Methods 5. Collections 6. Arrays 7. Strings 8. Metaprogramming 9. Standard Libraries Module 2. The Development Environment 10. Programming Guidelines in Julia 11. Performance Management 12. IDE and Debugging 13. Package Management 14. Deployment Module 3. Packages in Julia 15. Data Transformations 16. Text Analytics 17. Deep Learning

Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Download or read book Practical Julia written by Lee Phillips and published by No Starch Press. This book was released on 2023-10-31 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to use Julia as a tool for research, and solve problems of genuine interest—like modeling the course of a pandemic—in this practical, hands-on introduction to the language. The Julia programming language is acclaimed in scientific circles for its unparalleled ease, interactivity, and speed. Practical Julia is a comprehensive introduction to the language, making it accessible even if you’re new to programming. Dive in with a thorough guide to Julia’s syntax, data types, and best practices, then transition to craft solutions for challenges in physics, statistics, biology, mathematics, scientific machine learning, and more. Whether you’re solving computational problems, visualizing data, writing simulations, or developing specialized tools, Practical Julia will show you how. As you work through the book, you’ll: • Use comprehensions and generators, higher-level functions, array initialization and manipulation, and perform operations on Unicode text • Create new syntax and generate code with metaprogramming and macros, and control the error system to manipulate program execution • Visualize everything from mathematical constructs and experimental designs to algorithm flowcharts • Elevate performance using Julia’s unique type system with multiple dispatch • Delve into scientific packages tailored for diverse fields like fluid dynamics, agent-based modeling, and image processing Whether your interest is in scientific research, statistics, mathematics, or just the fun of programming with Julia, Practical Julia will have you writing high-performance code that can do real work in no time. Online Resources: Ready-to-run code samples, illustrations, and supplemental animations available at https://julia.lee-phillips.org.

Download or read book Julia for Data Science written by Anshul Joshi and published by Packt Publishing Ltd. This book was released on 2016-09-30 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the world of data science from scratch with Julia by your side About This Book An in-depth exploration of Julia's growing ecosystem of packages Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data sets Who This Book Is For This book is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to those competent in R and Python and wish to adopt Julia to improve their skills set in Data Science. It would be beneficial if the readers have a good background in statistics and computational mathematics. What You Will Learn Apply statistical models in Julia for data-driven decisions Understanding the process of data munging and data preparation using Julia Explore techniques to visualize data using Julia and D3 based packages Using Julia to create self-learning systems using cutting edge machine learning algorithms Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models Build a recommendation engine in Julia Dive into Julia's deep learning framework and build a system using Mocha.jl In Detail Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century). This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game. This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations. You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning. This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia. Style and approach This practical and easy-to-follow yet comprehensive guide will get you learning about Julia with respect to data science. Each topic is explained thoroughly and placed in context. For the more inquisitive, we dive deeper into the language and its use case. This is the one true guide to working with Julia in data science.

Download or read book Algorithms for Optimization written by Mykel J. Kochenderfer and published by MIT Press. This book was released on 2019-03-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.