Summary
In this chapter, we've discussed popular time-series machine learning libraries in Python. We then discussed and tried out a k-nearest neighbor algorithm with dynamic time warping for the classification of robotic failures. We talked about validation in time-series forecasting and we tried three different methods for forecasting COVID cases: Silverkite, Gradient Boosting with XGBoost, and ensemble models in Kats.