Julia 2019 Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Julia 2019 book. This book definitely worth reading, it is an incredibly well-written.
'One of a kind. Utterly fantastic.' Eoin Colfer on Tin David and Penny's strange new home is surrounded by forest. It's the childhood home of their mother, who's recently died. But other creatures live here ... magical creatures, like tiny, hairy Pog. He's one of the First Folk, protecting the boundary between the worlds. As the children explore, they discover monsters slipping through from the place on the other side of the cellar door. Meanwhile, David is drawn into the woods by something darker, which insists there's a way he can bring his mother back ...
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.
Fans of Far from the Tree, We Are Okay and Emergency Contact will love this epic, utterly unforgettable contemporary novel about a lost shipwreck, a missing piece of family history, and weathering the storms of life. The Larkin family isn't just lucky—they persevere. At least that's what Violet and her younger brother, Sam, were always told. When the Lyric sank off the coast of Maine, their great-great-great-grandmother didn't drown like the rest of the passengers. No, Fidelia swam to shore, fell in love, and founded Lyric, Maine, the town Violet and Sam returned to every summer. But wrecks seem to run in the family: Tall, funny, musical Violet can't stop partying with the wrong people. And, one beautiful summer day, brilliant, sensitive Sam attempts to take his own life. Shipped back to Lyric while Sam is in treatment, Violet is haunted by her family's missing piece—the lost shipwreck she and Sam dreamed of discovering when they were children. Desperate to make amends, Violet embarks on a wildly ambitious mission: locate the Lyric, lain hidden in a watery grave for over a century. She finds a fellow wreck hunter in Liv Stone, an amateur local historian whose sparkling intelligence and guarded gray eyes make Violet ache in an exhilarating new way. Whether or not they find the Lyric, the journey Violet takes—and the bridges she builds along the way—may be the start of something like survival. Epic, funny, and sweepingly romantic, The Last True Poets of the Sea is an astonishing debut about the strength it takes to swim up from a wreck.
One of The New York Times 10 Best Books of the Year National Book Award Finalist Finalist for the National Book Critics Circle John Leonard Prize Finalist for the Center for Fiction First Novel Prize Finalist for the New York Public Library's Young Lions Fiction Award National Best Seller "Splendidly imagined . . . Thrilling" --Simon Winchester "A genuine masterpiece" --Gary Shteyngart Spellbinding, moving--evoking a fascinating region on the other side of the world--this suspenseful and haunting story announces the debut of a profoundly gifted writer. One August afternoon, on the shoreline of the Kamchatka peninsula at the northeastern edge of Russia, two girls--sisters, eight and eleven--go missing. In the ensuing weeks, then months, the police investigation turns up nothing. Echoes of the disappearance reverberate across a tightly woven community, with the fear and loss felt most deeply among its women. Taking us through a year in Kamchatka, Disappearing Earth enters with astonishing emotional acuity the worlds of a cast of richly drawn characters, all connected by the crime: a witness, a neighbor, a detective, a mother. We are transported to vistas of rugged beauty--densely wooded forests, open expanses of tundra, soaring volcanoes, and the glassy seas that border Japan and Alaska--and into a region as complex as it is alluring, where social and ethnic tensions have long simmered, and where outsiders are often the first to be accused. In a story as propulsive as it is emotionally engaging, and through a young writer's virtuosic feat of empathy and imagination, this powerful novel brings us to a new understanding of the intricate bonds of family and community, in a Russia unlike any we have seen before.
"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
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.
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
Design and develop high-performance programs in Julia 1.0 Key FeaturesLearn the characteristics of high-performance Julia codeUse the power of the GPU to write efficient numerical codeSpeed up your computation with the help of newly introduced shared memory multi-threading in Julia 1.0Book Description Julia is a high-level, high-performance dynamic programming language for numerical computing. If you want to understand how to avoid bottlenecks and design your programs for the highest possible performance, then this book is for you. The book starts with how Julia uses type information to achieve its performance goals, and how to use multiple dispatches to help the compiler emit high-performance machine code. After that, you will learn how to analyze Julia programs and identify issues with time and memory consumption. We teach you how to use Julia's typing facilities accurately to write high-performance code and describe how the Julia compiler uses type information to create fast machine code. Moving ahead, you'll master design constraints and learn how to use the power of the GPU in your Julia code and compile Julia code directly to the GPU. Then, you'll learn how tasks and asynchronous IO help you create responsive programs and how to use shared memory multithreading in Julia. Toward the end, you will get a flavor of Julia's distributed computing capabilities and how to run Julia programs on a large distributed cluster. By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs. What you will learnUnderstand how Julia code is transformed into machine codeMeasure 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 Accelerate your code via the GPUUse tasks and asynchronous IO for responsive programsRun Julia programs on large distributed clustersWho this book is for This book is for beginners and intermediate Julia programmers who are interested in high-performance technical programming. A basic knowledge of Julia programming is assumed.
In this exciting sequel to The Mystery of Black Hollow Lane, Emmy's adventures continue as she deals with a sinister organization, a missing father, and secrets she's not sure who to trust with. After spending the summer at home in Connecticut, Emmy cannot wait to return to Wellsworth for the new school year and reunite with her best friends, Lola and Jack. Before she leaves Emmy receives a note from her father telling her to hide the remaining relics The Order of Black Hollow Lane are after—and to trust no one. When Lola is framed for a serious crime she didn't commit, Emmy knows that she and her friends are not safe. The Order wants Emmy to give up her father's location... if she doesn't, those she loves will pay the price. Emmy and Jack need to figure out a way to clear Lola's name without bending to the Order's sinister demands. And Emmy needs to figure out who she can trust with her secrets before it's too late.
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