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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
Author (1):
Rounak Banik Rounak Banik
Profile icon Rounak Banik
LinkedIn
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.
See other products by Rounak Banik

Table of Contents (9) Chapters

Preface 1. Getting Started with Recommender Systems 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

The Pandas library

Pandas is a package that gives us access to high-performance, easy-to-use tools and data structures for data analysis in Python.

As we stated in the introduction, Python is a slow language. Pandas overcomes this by implementing heavy optimization using the C programming language. It also gives us access to Series and DataFrame, two extremely powerful and user-friendly data structures imported from the R Statistical Package.

Pandas also makes importing data from external files into the Python environment a breeze. It supports a wide variety of formats, such as JSON, CSV, HDF5, SQL, NPY, and XLSX.

As a first step toward working with pandas, let's import our movies data into our Jupyter Notebook. To do this, we need the path to where our dataset is located. This can be a URL on the internet or your local computer. We highly recommend downloading the data...

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Authors (1)

Profile icon Rounak Banik
LinkedIn
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.
See other products by Rounak Banik

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