This is one of Deep learning nanodegree major projects. In this project, I have built a neural network from scratch to carry out a prediction problem on a real dataset! By building a neural network from the ground up, I got a much better understanding of gradient descent, backpropagation, and other concepts that are important to know before moving to higher-level tools such as PyTorch or Keras.
The data comes from the UCI Machine Learning Database
iterations = 5500
learning_rate = 0.6
hidden_nodes = 10
output_nodes = 1