"If we have a project and you're saying okay I can do that. That's not the project we want. The projects that say [...] I don't know how to do that. Those are the things we want because through that curiosity you'll reach a level that you didn't think was possible." -Kobe Bryant
The main goal of this project is to apply the Machine Learning methods we studied this semester and reflect the knowledge we have gained since the previous Data Science course.
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Hotel Booking Demand Dataset
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Fashion-MNIST Dataset
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Dogs vs. Cats Dataset
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Using Hand Movements to Predict Interpersonal Physical Alignment
For additional information you can visit the PDF file in this repository.
- Hands-On Machine Learning (Second Edition) by Aurélien Géron manages to simplify complex theories and give hands-on examples with Python implementations.
- The Joblib library (which was also recommended in the book mentioned above) provides a way to save and load data, models, predictions, etc. This library is perfect for large datasets that take a long time to run and provided an efficient way to save and load my progress. Evidently, this helped me save time and I was able to perform more thorough model tuning and training!
Note: More resources are listed in the end of each notebook.