In this project, we have done comparative analysis of various rating prediction methods on MovieLens100k[1] dataset.
Initially, extensive Exploratory Data Analysis (EDA) is done to visualise feature distributions and pick informative characteristics for implementation.
While implementing, we have considered DeepFM, Deep & Cross Networks (DCNs) with stacked, parallel architecture along with Low-rank techniques and Deep Neural Networks (DNNs). Furthermore, variations to RMSE for each model based on different values for hyperparameters are visualised.