In this section, we will utilize Keras as a deep learning framework in order to build our models. Keras can easily be installed by using either pip (pip install keras) or conda (conda install -c conda-forge keras). In order to build the neural networks, we must first understand our data. The MovieLens dataset consists of almost 100,000 samples and 4 different variables:
- userId: A numeric index corresponding to a specific user
- movieId: A numeric index corresponding to a specific movie
- rating: A value between 0 and 5
- timestamp: The specific time when the user rated the movie
A sample from the dataset is depicted in the following table. As is evident, the dataset is sorted by the userId column. This can potentially create overfitting problems in our models. Thus, we will shuffle the data before any split happens. Furthermore, we will not utilize...