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Codeology Spring 2020 Project: Data Science project creating the ultimate NBA scout using Machine Learning.

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Ballin With Data | Codeology Spring 2020 Project

Project Leaders: Calvin Chen, Matt Hashimoto

Project Developers: Trevor Baba, Ethan Chen, Katherine Peng, Krishna Ravi, John Um, Taylor Yoo

Background

Ballin with Data is a Data Science project by Matt Hashimoto and Calvin Chen, creating the ultimate NBA scout using ML. We got NCAA and NBA data from the sportsreference API (documentation here), and used ML models including Linear Regression, Neural Networks, K-Means Clustering, Decision Trees, and Random Forests in order to project an NBA player’s rookie stat line based on their college stats. We then used the anvil webapp builder to create a UI to go along with our NBA Rookie Stat predictor, which was housed in a Jupyter Notebook.

Webapp link here (disclaimer: due to Anvil uplink frequently disconnecting, the frontend and backend are likely not connected. Replace the Anvil endpoint with your own on the Anvil platform).

Google Drive with Slides + Resources: Balling with Data

If you have any questions or see any issues, feel free to post an issue above, and we will address it as soon as we can. Thank you!


Set up for local development

To get started, git clone the repo onto your local machine.

git clone https://github.com/claalmve/Ballin-With-Data.git

Then install the different packages from the requirements.txt file.

pip3 install -r requirements.txt

To launch the notebook, use the following command:

jupyter notebook

You're all set! Have fun!

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Codeology Spring 2020 Project: Data Science project creating the ultimate NBA scout using Machine Learning.

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