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* [Suiron](https://github.com/kendricktan/suiron/) - Machine Learning for RC Cars.
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* [Introduction to machine learning with scikit-learn](https://github.com/justmarkham/scikit-learn-videos) - IPython notebooks from Data School's video tutorials on scikit-learn.
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* [Practical XGBoost in Python](http://education.parrotprediction.teachable.com/p/practical-xgboost-in-python) - comprehensive online course about using XGBoost in Python.
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* [Introduction to Machine Learning with Python](https://github.com/amueller/introduction_to_ml_with_python) - Notebooks and code for the book "Introduction to Machine Learning with Python"
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* [Pydata book](https://github.com/wesm/pydata-book) - Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
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<a name="python-neural-networks"></a>
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#### Neural Networks
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