Hyperparameter tuning is choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a model argument whose value is set before the learning process begins. The key to machine learning algorithms is to chose the optimal pair/pairs of hyperparameters. For our project we just focus on tuning two parameters of the model: 1. Learning rate 2. Dropout