End to End Recommendation System | Content based | collaborative filtering | Amazon recommendation

A recommendation engine is a system or algorithm that analyzes user data and provides personalized suggestions or recommendations for items or content that the user may be interested in.
These recommendations are based on various factors such as the user's preferences, historical behavior, demographic information, and similarities to other users.

Recommendation engines are commonly used in e-commerce, OTT platforms,
social media, and other online services to enhance user experience and engagement. They help users discover new products, movies, music, articles, or any other items that align with their interests.

Note: Before executing this notebook make sure you have downloaded the kaggle.json API token file,
because while downloading the dataset using the Opendatasets library it will ask for a Kaggle username and secret key.

Google Colab link : https://colab.research.google.com/dri...

Kaggle dataset link: https://www.kaggle.com/datasets/irvif...

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