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 performing inferential statistics, and will reveal hidden patterns and trends using data mining. This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations.

You will then delve into the world of Deep learning in Julia and will understand the framework, Mocha.jl with which you can create artificial neural networks and implement deep learning.

This book addresses the challenges of real-world data science problems, including data cleaning, data preparation, inferential statistics, statistical modeling, building high-performance machine learning systems and creating effective visualizations using Julia.

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Spis treści

Julia for Data Science. high-performance computing simplified eBook -- spis treści

• 1. The Groundwork: Julia’s environment
• 2. Data Munging
• 3. Data Exploration
• 4. Deep dive into inferential statistics
• 5. Making sense of data using visualization
• 6. Supervised Machine learning
• 7. Unsupervised Machine learning
• 8. Creating ensemble models
• 9. Time Series
• 10. Collaborative filtering and recommendation system
• 11. Deep Learning