This is an implementation of MLP by just using NumPy to classify handwritten digits and clothes. It consists of four different models, each using the sigmoid or Tanh activation function and the cross-entropy or mean squared error loss function. All features are standardized first, and all models are trained using NADAM optimization and Mini-batch gradient descent.