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Julia for Data Science

You're reading from  Julia for Data Science

Product type Book
Published in Sep 2016
Publisher Packt
ISBN-13 9781785289699
Pages 346 pages
Edition 1st Edition
Languages
Author (1):
Anshul Joshi Anshul Joshi
Profile icon Anshul Joshi

Table of Contents (17) Chapters

Julia for Data Science
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
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. Introduction to Deep Learning

About the Author

Anshul Joshi is a data science professional with more than 2 years of experience primarily in data munging, recommendation systems, predictive modeling, and distributed computing. He is a deep learning and AI enthusiast. Most of the time, he can be caught exploring GitHub or trying anything new on which he can get his hands on. He blogs on anshuljoshi.xyz.

I'd like to thank my parents, who have been really supportive throughout, my professors, who helped me during my days at university and got me where I am, and my friends, who were very understanding. A big thanks to the Julia community. These people are amazing and are the rockstars of our generation.

I would also like to thank Packt Publishing and the editors for helping me throughout. A special thanks to Sébastien Celles; his expertise and reviews really helped me improve the book.

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