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Hands-On Recommendation Systems with Python

You're reading from Hands-On Recommendation Systems with Python

Product type Book

Published in Jul 2018

Publisher Packt

ISBN-13 9781788993753

Pages 146 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Rounak Banik

Table of Contents (9) Chapters

Preface

Getting Started with Recommender Systems

Manipulating Data with the Pandas Library

Building an IMDB Top 250 Clone with Pandas

Building Content-Based Recommenders

Getting Started with Data Mining Techniques

Building Collaborative Filters

Hybrid Recommenders

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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/2uOHwcd .

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Authors (1)

Rounak 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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