- This repo is the work of Skyler Tran, Clay Harper, and Taylor Slaton for Machine Learning course (Spring 2020)
- Each notebook file is one assignment which includes online sources, specific datasets and our work to go through and analyze them:
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Exploring Table Data: Genetic Variant Classifications (Predict whether a variant will have conflicting clinical classifications) - https://www.kaggle.com/kevinarvai/clinvar-conflicting
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Images processing: The Car Connection Picture Dataset (Business Understanding is inside this notebook) - https://www.kaggle.com/prondeau/the-car-connection-picture-dataset
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Extending Logistic Regression: Genetic Variant Classifications (In this notebook, we extended our work from notebook 1 above and used Linear Regression to predict missing data) - https://www.kaggle.com/kevinarvai/clinvar-conflicting
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skylert7/Machine_Learning_SMU
Machine Learning Homework (Spring 2020) - only finished work is posted here. Our team uses Google Colab for developing work.
Jupyter Notebook