Developing a Netflix Show Recommender with User Interface in Google Colab

Author(s): Surabhi Anuradha

Originally published on Towards AI.

Developing a Netflix Show Recommender with User Interface in Google Colab

“Tired of spending hours searching for the perfect Netflix show? What if you had a personalized recommendation system at your fingertips? In this article, we’ll guide you through building a simple yet effective Netflix show recommender with an intuitive user interface — all within Google Colab.”

This article explains the process of creating a personalized Netflix show recommender using Google Colab. It begins by introducing the significance of recommendation systems, specifically focusing on collaborative and content-based filtering methods. The author details the environment setup and the dataset used, emphasizing data preparation techniques, including text tokenization and removal of unnecessary information. Through visualizations like word clouds, common genres and themes are analyzed. The article further discusses implementing a Word2Vec model for improving recommendations by assessing similarity between shows based on titles, genres, and descriptions. It concludes by describing a user-friendly interface that enhances user interaction, providing quick and personalized recommendations based on user-selected shows.

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Published via Towards AI