Practical Julia

Applied 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. Additional online resources include ready-to-run code samples, illustrations, and supplemental animations.

Applied 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. Additional online resources include ready-to-run code samples, illustrations, and supplemental animations.