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Partie I

1. Aggarwal, Charu C. 2018. Machine Learning for Text. Springer.
2. Lane, Hobson, Howard, Cole, Hapke, Hannes Maax. 2019. Natural Language Processing in Action: Understanding, analyzing, and generating text with Python. Manning.
3. Dalianis, Hercules. 2018. Clinical Text Mining: Secondary use of Electronic Patient Records. Springer.

Partie II

1. Alpaydin, Ethem. 2004. Introduction to Machine Learning. MIT Press.
2. Bishop, Christopher M. 2011. Pattern Recognition and Machine Learning. Springer.
3. Duda, Richard O., Hart, Peter E., Stork, David G. 2001. Pattern Classification. John Wiley & Sons.
4. Haton, Jean-Paul, Cerisara, Christophe, Fohr, Dominique, Laprie, Yves, Smaïli, Kamel. 2006. Reconnaissance automatique de la parole : du signal à son interprétation. Dunod.
5. Huang, Xuang, Acero, Alex, Hon, Hsiao-Wuen. 2001.  Spoken Language Processing: A Guide to Theory, Algorithm, and System Development. Prentice-Hall.
6. Juravsky, Daniel, Martin, James H.  2019. Speech and Language Processing. La première ébauche de cette 3eme édition est disponible gratuitement en ligne (https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf).
7. McTear, Michael F. 2004. Spoken Dialogue Technology: Toward the Conversational User Interface. Springer.

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