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Literature and readings

완료 조건
The main literature for machine learning:
  • James, G., Witten, D., Hastie, T., Tibshirani, R. and Taylor, J., 2023. An Introduction to Statistical Learning: With Applications in Python. New York: Springer. Freely available at https://www.statlearning.com/  (the same book exists for R)

Further readings:

  • Kevin P. Murphy: Probabilistic Machine Learning: An Introduction. MIT Press, 2022
  • Friedman, J., Hastie, T., & Tibshirani, R. (2001). The elements of statistical learning. Springer, Berlin. (freely available)
  • Jurafsky, Daniel and James, Martin (2024): Speech and Language Processing, 3rd edition in progress, freely available
  • Richard S. Sutton and Andrew G. Barto: Reinforcement Learning, An Introduction, 2nd edition, MIT Press, 2018, freely available

  • Kevin P. Murphy: Probabilistic Machine Learning: Advanced Topics. MIT Press, 2023

    • Reeves - 2010 - Genetic Algorithms.pdf Reeves - 2010 - Genetic Algorithms.pdf
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