Bicycle sharing system forecast

This project use a neural network to predict daily bike rental ridership.

See the jupyter notebook

Motivation

Implement the backpropagation algorithm for a neural network.

Built With

• Python 3 - Language
• Anaconda - Python Data Science Platform
• Jupyter notebook - Web application that allows to create documents that contain live code

Dataset

The core data set is related to the two-year historical log corresponding to years 2011 and 2012 from Capital Bikeshare system, Washington D.C., USA which is publicly available in http://capitalbikeshare.com/system-data.

For more information read this

Getting Started

Prerequisites

1. Download and install Anaconda
2. Update Anaconda

$ conda upgrade conda 
$ conda upgrade --all 

Install

1. Clone and enter into the project's root directory by command line

$ git clone https://github.com/machine-learning-experiments/bicycle-sharing-forecast.git

2. Create and activate enviroment

$ conda env create -f enviroment.yaml 
$ conda activate bicycle-sharing-forecast 

or

conda create --name bicycle-sharing-forecast python=3
source activate bicycle-sharing-forecast
conda install numpy matplotlib pandas jupyter notebook

3. Start jupyter notebook

$ jupyter notebook 

4. Your browser will open showing a list of files, click on the bicycle_sharing_neural_network.ipynb notebook file

Author

Lorival Smolski Chapuis

This project was developed during the deep-learning nanodegree from Udacity