World Business StrategiesServing the Global Financial Community since 2000

Suggested Reading List

Introduction and further reading:

  • Friedman, J., Hastie, T., & Tibshirani, R. (2009). The elements of statistical learning. vol. 2. Springer.
  • Murphy, K., (2012). Machine Learning, a Probabilistic Perspective. MIT press.
  • Efron, B., & Hastie, T. (2016). Computer age statistical inference (Vol. 5). Cambridge University Press.

Module 1:

Practical

  • Géron, A. (2017). Hands-on machine learning with Scikit-Learn and TensorFlow: concepts, tools, and techniques to build intelligent systems. ” O’Reilly Media, Inc.”.

Theorectical

  • Shalev-Shwartz, S., & Ben-David, S. (2014). Understanding machine learning: From theory to algorithms. Cambridge university press.
  • Mohri, M., Rostamizadeh, A., & Talwalkar, A. (2018). Foundations of machine learning. MIT press.
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