Some of the techniques presented here are used in the next two modules focusing on synthetic data. Before diving into these techniques, Vincent will discuss data cleaning automation, data animation (data videos), and simplicity (illustrated by case study: marketing attribution without math). The new machine learning techniques introduced include:

Generic unsupervised regression: covers all regression techniques and more, including an alternative to K-means.
Time series with double period (mimicking ocean tides).
Interpretable regression.
Simplified ensemble method, alternative to XGBoost.
Superimposed spatial point processes and alternative to GMM and GAN.

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