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Predicting Bike-sharing Demand Using Machine Learning with AutoGluon

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Predicting Bike-sharing Demand Using Machine Learning with AutoGluon

Project Description:

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Bike-sharing demand is highly relevant to related problems companies encounter, such as Uber, Lyft, and DoorDash. Predicting demand not only helps businesses prepare for spikes in their services but also improves customer experience by limiting delays.

Setup

For some reason, this project runs the best with Python3.7 with zero errors.

  • Setup Environment - Python 3.7 with notebook (If you are using locally) :
wget https://www.python.org/ftp/python/3.7.4/Python-3.7.4.tgz && tar -xvf Python-3.7.4.tgz && cd Python-3.7.4/ && ./configure --prefix=$HOME/Python37 && make && make install && cd .. && rm -rf Python-3.7.4.tgz && sudo add-apt-repository ppa:deadsnakes/ppa && sudo apt-get update && sudo apt-get install python3.7 && sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 && virtualenv -p ~/Python3.7/bin/python3 .venv && source .venv/bin/activate && pip install notebook && ipython kernel install --user --name .venv --display-name "Python 3.7" && jupyter notebook

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