English | 2017 | ISBN: 978-1785883279 | 316 Pages | PDF | 10 MB
Learn Julia language for data science and data analytics
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.
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
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