Description
Book SynopsisApplied Julia provides a comprehensive, hands-on language introduction that's packed with examples leveraging real scientific libraries used by researchers in various fields. Solve problems of genuine interest, such as modeling the course of a pandemic, and learn to use Julia as a tool for research. The Julia programming language can be used to write all types of applications, but its features are especially powerful for numerical analysis and computational science. Applied Julia shows readers how to take advantage of Julia's particular strengths, as well as how to write effective and efficient programs. The book takes Julia novices from their very first steps to writing real-world applications for use in fields such as biology, physics, math, statistics, and machine learning. Not only will readers develop the Julia knowledge needed for solving computational problems, but they'll also learn how to explore and visualise data, solve equations, write simulations, and create libraries. Ad
Trade Review"A great starting point for the reader’s journey into Julia - with the first part covering the fundamentals of the language and second part diving into a variety of different scientific disciplines."
—Viral Shah, co-creator of the Julia programming language and CEO of JuliaHub
"This is a nice deep dive that covers a lot of ground, from the basics on how to define arrays and use the type system all the way to biochemical modeling and scientific machine learning. Lee gives a very nice in-depth treatment, showing not only the most standard ways to do things, but also some different library options along with a good explanation of the pros and cons to the choices. I think this is a great book for any Julia user's shelf."
—Christopher Rackauckas, Applied Mathematics Instructor, Massachusetts Institute of Technology
"Practical Julia is clear, concise, and complete, exactly what you want in an introductory book. It’s also really interesting; the author has an engaging voice and a knack for good examples. Along with a general introduction to Julia, he provides real-world illustrations of applying Julia to specific problems in biology, physics, statistics, machine learning, and other areas. Highly recommended."
—David Chappell, Principal of Chappell & Associates
Table of ContentsIntroduction
PART I: LEARNING JULIAChapter 1: Getting Started
Chapter 2: Language Basics
Chapter 3: Modules and Packages
Chapter 4: The Plotting System
Chapter 5: Collections
Chapter 6: Functions, Metaprogramming, and Errors
Chapter 7: Diagrams and Animations
Chapter 8: The Type System
PART II: APPLICATIONSChapter 9: Physics
Chapter 10: Statistics
Chapter 11: Biology
Chapter 12: Mathematics
Chapter 13: Scientific Machine Learning
Chapter 14: Signal and Image Processing
Chapter 15: Parallel Processing
Index
