▪️ Understand machine learning algorithms, models, and core machine learning concepts
▪️ Classify examples with classifiers, and quantify examples with regressors
▪️ Realistically assess performance of machine learning systems
▪️ Use feature engineering to smooth rough data into useful forms
▪️ Chain multiple components into one system and tune its performance
▪️ Apply machine learning techniques to images and text
▪️ Connect the core concepts to neural networks and graphical models
▪️ Leverage the Python scikit-learn library and other powerful tools