Refine your deep learning model

As part of my own learning, continuing from Part 1 and trying to improve our neural network model, we will use some of the well-known machine learning techniques mentioned on TensorFlow. In the previous article, we saw certain problems with our training. Here, we will address them and see if our results improve as we go. A model is considered to overfit when it performs with great accuracy on the training data (data used for training the model), but when evaluated against a test or unseen data set, it performs rather poorly. This happens because our model has overfit the data.