Important Topics in Machine Learning

Start with the basics

• A few useful things to know about machine learning

• Parameters and hyperparameters (Andrew Ng's video)

• Grid search for model tuning

Discretization

• An Introduction to Discretization Techniques for Data Scientists Feature Engineering: 4 Discretization Techniques to Learn (with Python examples)

Feature Engineering Libraries

• Feature-engine

• Scikit-learn

• fsfresh

• Featuretools

• PyAudioAnalysis

Cross validation

• Cross validation in machine learning

• Nested cross validation

Dataset Shift

• Understanding dataset shift

• Investigate dataset shift with python code

Imbalanced Data

• Resampling with Python code [Example 1][Example 2]

• How does the class_weight in scikit-learn work? "class_weight="balanced" basically means replicating the smaller class until you have as many samples as in the larger one, but in an implicit way"

Performance Measures

• Matthew's Correlation Coefficient [Link1] [Link2]