Multi - Layer Perceptron Neural Network using Pytorch

Movie Recommendation System implemented using Pytorch in Python

In this project, the MovieLens dataset was used to classify movies and recommend the best option per user. The repo is organised as follows:

• dataset_preparation.ipynb: Jupyter notebook that does data preprocessing
• matrix_factorization.ipynb: Jupyter notebook that uses the embeddings technique provided by Pytorch framework to factorize the tabular matrix created by the data preprocessing notebook
• mlp.ipynb: Jupyter notebook where the multi - layer perceptron is implemented
• u.data: The dataset used in the project

In this project, there was an experiment where matrix factorization was both carried out by a multi - layer perceptron and an embeddings neural network. The result was much better using the embeddings neural network. Finally, there is a Jupyter cell where a custom keras - like neural network fitting was implemented. This cell displays live progress of the neural network while it's training.