This article gives you the best Julia machine learning book. There are many good books, but reading through top lists of best machine learning books for Julia takes time and effort, and you may not even find what you are looking for. Fear not though. We did the reading for you. We are happy to present you with the winner below!
Julia and Why it’s so Good
Julia is a high level and highly effective programming language made for data scientists and engineers. While it’s a general purpose language that can be used for almost anything, it really shines when it comes to data science and numerical computation. It a lot of similarities to languages such as R, Python, Matlab and so on.
The Best Book for doing Machine Learning with the Julia Programming Language
You may have guessed it. The winner is no other that the exceptionally well written Julia Programming Projects by Adrian Salceanu. Not only is this book the best Julia machine learning book out there, it’s also one of the most popular books for learning Julia programming in general.
The full title of the book is “Julia Programming Projects: Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web”. It gives a fairly short but thorough introduction to the programming language. It goes on to demonstrate how to analyze datasets using DataFrames like many know from python and pandas. After a brief start, the book takes you through great examples with both supervised- and unsupervised machine learning. It will teach you (among other things) how to build a recommender system from scratch, how to manipulate and predict time series data, how to use unsupervised machine learning to cluster business data and much more. Finally Julia Programming Projects will go over development, documenting and testing to make sure you can some most of the real-life Julia problems you may encounter.
Table of Contents
- Analysis and manipulation of datasets in Julia
- Julia application development for different platforms
- Supervised machine learning algorithms
- Unsupervised machine learning algorithms
- Make predictions on time series data and more
- Build beautiful visualizations
- Understand and utilize Julia’s strengths compared to other languages
Who Will Get the Most out of This Book
This book is mainly written for data scientists, machine learning engineers, business analysts, and statisticians who want to build machine learning applications in Julia. Some prior knowledge in data science or app development is helpful but not required. However, basic programming skills is expected to get the most out of the book.
Other Great Books for Machine Learning in Julia
We understand that the needs and proficiency level varies between people, so here are some other great picks if you are looking for more books.
Julia for Machine Learning: Very focus on machine learning, not so much on Julia in general. Great if you know Julia already.
Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages: A beginner friendly approach to machine learning in Julia. Great and cheap book to get you started quickly.
Hope you liked our choice for the best Julia programming machine learning book. If you wanna read more books about machine learning frameworks like TensorFlow, you can find them here.