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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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Setting up the environment

Before we start coding, we should probably set up our development environment. For data scientists and analysts using Python, the Jupyter Notebook is, by far, the most popular tool for development. Therefore, we strongly advise that you use this environment.

We will also need to download the pandas library. The easiest way to obtain both is to download Anaconda. Anaconda is a distribution that comes with the Jupyter software and the SciPy packages (which includes pandas).

You can download the distribution here: https://www.anaconda.com/download/.

The next step is to create a new folder (I'm going to name it RecoSys) in your desired location. This will be the master folder that contains all the code we write as part of this book. Within this folder, create another folder named Chapter2, which will contain all the code we write as part of this chapter...

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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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