Movie Recommendation System With Python And Pandas: Data Project

In this project walkthrough, we'll learn how to create a movie recommendation system using Jupyter, Python, and Pandas. By the end, we'll be able to type the name of a movie into an input box, and instantly get recommendations for other movies we might like. This is an exciting project that can go into a portfolio, or help you learn.

We'll start with the MovieLens 25M dataset, which contains movie reviews and ratings. Then, we'll build a search engine to find a specific movie title in our data. We'll then be able to create a recommendation engine to recommend specific movies.

You can download the data here - https://files.grouplens.org/datasets/... .

And you can view the code for this project here - https://github.com/dataquestio/projec... .

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Chapters

00:00 - Introduction
01:36 - Reading in our movie data with pandas
02:41 - Cleaning movie titles with regex
04:20 - Creating a tfidf matrix
08:21 - Creating a search function
13:10 - Building an interactive search box with Jupyter
18:05 - Reading in movie ratings data
19:29 - Finding users who liked the same movie
25:51 - Finding how much all users like movies
29:06 - Creating a recommendation score
32:02 - Building a recommendation function
33:38 - Creating an interactive recommendation widget
37:05 - Next steps

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