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.