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Deep Learning for Predicting Bike Sharing Ridership

In this project, we build a neural network from scratch to predict the number of bikeshare users in a given day. By building a neural network from the ground up, we'll have a much better understanding of gradient descent, backpropagation, and other concepts that are important to know before we move to higher level tools such as PyTorch.

This project is a part of Udacity Deep Learning Nanodegree.

The data comes from the UCI Machine Learning Database.

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