Recommender System with Surpriselib

Film Recommender Project:

This project includes code and insight from a 2018 LinkedIn Learning Course titled "Building Recommender Systems with Machine Learning and AI". The code example provided represents a user-based and an item-based collaborative filtering.

Content-Based Filtering:

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Collaborative Filtering: User-Based & Item-Based

User-Based Collaborative Filtering:

This type of recommender system leverages the behavior and interests of other people (in this case, other movie veiwers) to inform what you might enjoy. This entails finding other viewers like me and recommending movies they liked. This solution makes recommendations based on other people's collaborative behavior.

Item-Based Collaborative Filtering:

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Contents

Notebook 00: Install Surprise
Notebook 01: Load MovieLens Data
Notebook 01: