Best 10 julia language book data science

Best 10 Julia Programming Language Books for Data Science- 2020

Julia is a high-level flexible, open-source dynamic programming language. The language has been developed for scientific and numerical computing. You can use this language for data mining, business analytics, data analysis, machine learning, and visualization.

In this post, I am going to share with you the list of the books of Julia Programming Language that are effective for Students, Research Scholar, and Data Scientist.

1. Julia for Data Science by Zacharias Voulgaris, Technics Publications- Link

2. Data Science with Julia by Paul D McNicholas, Peter A Tait, CRC Press –Link

3.Julia 1.0 Programming: Dynamic and high-performance programming to build fast scientific applications, 2nd Edition, Packt Publishing- Link

4. Think Julia How to Think Like a Computer Scientist by Ben Lauwens, Allen B. Downey, O’Reilly Media (paper version)- Link

5.Julia 1.0 Programming Cookbook by Bogumil Kaminski, Przemyslaw Szufel, Packt Publishing- Link

6.Julia High Performance: Optimizations, distributed computing, multithreading, and GPU programming with Julia 1.0 and beyond, 2nd Edition- Link

7. Julia 1.0 Programming Complete Reference Guide: Discover Julia, a high-performance language for technical computing, Packt Publishing -Link

8. Learning Julia: Build high-performance applications for scientific computing, Packt Publishing- Link

9. Hands-On Design Patterns and Best Practices with Julia: Proven solutions to common problems in software design for Julia 1.x, Packt Publishing – Link

10. Julia Programming Projects: Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web, by Adrian Salceanu, Packt Publishing – Link

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