I wanted to create a recommendation system that uses ML to try to compare it with other recommendation systems.

What it does

It takes a set of movies rated by the user, and recommends a movie to the user based on his or her ratings, providing basic information about it. It uses the LASSO method to train the model and obtain the results.

How I built it

I used scikit-learn ML package to fit the data, and pandas to analyze it and treat it

Challenges I ran into

Integrating the code form the jupyter notebook and the frontend

Accomplishments that I'm proud of

Being able to train a model with few data and obtaining reasonable results, as well as having worked with machine learning for the very first time

What's next for Your next movie

Trying to create a frontend which makes it more usable for non-technical users, as well as providing more information about the movies and giving the user the chance to restrict the search to a particular movie genre.

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