Overview of important libraries for day-to-day work with machine learning in Python:



• Pandas (http://pandas.pydata.org/) (data loading and filtering)



• Seaborn (https://seaborn.pydata.org/) (visualization)



• Scikit-learn (http://scikit-learn.org/) (dataset preparation, dimensionality reduction, simple models)



• Keras (https://keras.io/) (deep learning / neural networks)



We'll start from an interesting raw dataset and quickly get to cool visualizations and predictive models.