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Preliminary Reading


General Reading

  • Nate Silver (2013). The Signal and the Noise: The Art and Science of Prediction. Penguin

  • Sharon Bertsch Mcgrayne (2011).The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy. Yale University Press

Course Specific Reading
  • Bishop, C. Pattern Recognition and Machine Learning (2007). Students should read Chapter 2 "Probability distributions" and solve the exercises in that chapter, starting with the easy ones and then moving to the more difficult ones

  • Jurafsky, D & Martin, J. (2008). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Prentice Hall (2nd ed.). Section II on ‘Speech’

  • P. Taylor (2009). Text-to-Speech Synthesis, Cambridge University Press

  • Murphy, K. P. (2012) Machine Learning: A probabilistic perspective. Chapters 1-8

  • Ghahramani, Z. (2013) Bayesian nonparametrics and the probabilistic approach to modelling. Philosophical Transactions of the Royal Society A.

MLSALT1 Introduction to Machine Learning -- Preparatory Material