I built my first neural network.
The goal was to predict daily bike rental ridership using a dataset of bike rentals. The data comes from the UCI Machine Learning Database.
The network has two layers, one hidden layer and one output layer. I chose to use the sigmoid function for activations. Deep learning techniques used in this project include Gradient Descent, Forward Propogation and Backpropogation. The code is written in Python 3 with Python packages numpy, pandas, and matplotlib and is presented via Jupyter Notebook.