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Hands-On Recommendation Systems with Python

You're reading from Hands-On Recommendation Systems with Python Start building powerful and personalized, recommendation engines with Python

Product type Paperback

Published in Jul 2018

Publisher Packt

ISBN-13 9781788993753

Length 146 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Rounak Banik

View More author details

Table of Contents (9) Chapters

Preface

1. Getting Started with Recommender Systems FREE CHAPTER

2. Manipulating Data with the Pandas Library

3. Building an IMDB Top 250 Clone with Pandas

4. Building Content-Based Recommenders

5. Getting Started with Data Mining Techniques

6. Building Collaborative Filters

7. Hybrid Recommenders

8. Other Books You May Enjoy

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Technical requirements

You will be required to have Python installed on a system. Finally, to use the Git repository of this book, the user needs to install Git.

The code files of this chapter can be found on GitHub:
https://github.com/PacktPublishing/Hands-On-Recommendation-Systems-with-Python .

Check out the following video to see the code in action:

http://bit.ly/2JTtg6t .

You have been reading a chapter from

Hands-On Recommendation Systems with Python

Published in: Jul 2018

Publisher: Packt

ISBN-13: 9781788993753

© 2018 Packt Publishing Limited All Rights Reserved

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Authors (1)

Banik

Banik

Rounak Banik is a Young India Fellow and an ECE graduate from IIT Roorkee. He has worked as a software engineer at Parceed, a New York start-up, and Springboard, an EdTech start-up based in San Francisco and Bangalore. He has also served as a backend development instructor at Acadview, teaching Python and Django to around 35 college students from Delhi and Dehradun. He is an alumni of Springboard's data science career track. He has given talks at the SciPy India Conference and published popular tutorials on Kaggle and DataCamp.

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