Additional Resources

Exercises & Cheat Sheet

If you haven’t already done so, have a look at:

  • The programming exercises, to get your hands dirty and apply what you’ve learned.

  • The cheat sheet, which includes a step-by-step guide on how to solve a data science problem (incl. code snippets).

Using ML in Production

If you want to learn more about how to use ML in production, including topics like:

  • deploying a learned model

  • detecting data & concept drift

  • monitoring and retraining a model after deployment

then checkout the Coursera specialization Machine Learning Engineering for Production (MLOps)!

Textbooks: theoretical background (i.e. math!)
  • Pattern Recognition and Machine Learning by Christopher M. Bishop (2006)

  • Elements of Statistical Learning by T. Hastie, R. Tibshirani, J. Friedman (2009)

  • Deep Learning by I. Goodfellow, Y. Bengio, A. Courville (2016)

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