Explore the world of data science from scratch with Julia by your side

About This Book

• An in-depth exploration of Julia's growing ecosystem of packages
• Work with the most powerful open-source libraries for deep learning, data wrangling, and data visualization
• Learn about deep learning using Mocha.jl and give speed and high performance to data analysis on large data sets

Who This Book Is For

This book is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to those competent in R and Python and wish to adopt Julia to improve their skills set in Data Science. It would be beneficial if the readers have a good background in statistics and computational mathematics.

What You Will Learn

• Apply statistical models in Julia for data-driven decisions
• Understanding the process of data munging and data preparation using Julia
• Explore techniques to visualize data using Julia and D3 based packages
• Using Julia to create self-learning systems using cutting edge machine learning algorithms
• Create supervised and unsupervised machine learning systems using Julia. Also, explore ensemble models
• Build a recommendation engine in Julia
• Dive into Julia’s deep learning framework and build a system using Mocha.jl

In Detail

Julia is a fast and high performing language that's perfectly suited to data science with a mature package ecosystem and is now feature complete. It is a good tool for a data science practitioner. There was a famous post at Harvard Business Review that Data Scientist is the sexiest job of the 21st century. (https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century).

This book will help you get familiarised with Julia's rich ecosystem, which is continuously evolving, allowing you to stay on top of your game.

This book contains the essentials of data science and gives a high-level overview of advanced statistics and techniques. You will dive in and will work on generating insights by performin