Книги з теми "Apprentissage de représentations (intelligence artificielle)"
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Programme de recherche coordonnée-groupe de recherche coordonnée. Journées nationales. Intelligence artificielle: Actes des. [Lieu de publication non identifié]: Teknea, 1988.
Kodratoff, Yves. Apprentissage symbolique: Une approche de l'intelligence artificielle. Toulouse (France): Cépaduès-éditions, 1993.
Agnès, Guillot, and Daucé Emmanuel, eds. Approche dynamique de la cognition artificielle. Paris: Hermès science publications, 2002.
Alliot, Jean-Marc. Intelligence artificielle et informatique théorique. Toulouse: Cépaduès-éd., 1994.
Fischler, Martin A. Intelligence: The eye, the brain, and the computer. Reading, Mass: Addison-Wesley, 1987.
Nigel, Ford. How machines think: A general introduction to artificial intelligence ; illustrated in prolog. Chichester [West Sussex]: Wiley, 1987.
N, Kanal Laveen, Levitt Tod S, and Lemmer John F, eds. Uncertainty in artificial intelligence 3. Amsterdam: North-Holland, 1989.
1951-, Mitchell Tom M., Carbonell Jaime G, and Michalski Ryszard S. 1937-, eds. Machine learning: A guideto current research. Boston, (Mass.): Kluwer Academic, 1986.
1951-, Mitchell Tom M., Carbonell Jaime G, and Michalski Ryszard Stanislaw 1937-, eds. Machine learning: A guide to current research. Boston: Kluwer Academic Publishers, 1986.
Pratt, Vernon. Thinking machines: The evolution of artificial intelligence. Oxford, UK: B. Blackwell, 1987.
1962-, Mitra Sushmita, ed. Introduction to machine learning and bioinformatics. Boca Raton: Chapman & Hall/CRC, 2008.
1962-, Mitra Sushmita, ed. Introduction to machine learning and bioinformatics. Boca Raton: CRC Press, 2008.
Pollock, John L. How to build a person: A prolegomenon. Cambridge, Mass: MIT Press, 1989.
Mitchell, Tom M. sfafas. New York: McGraw-Hill, 1997.
Hutchinson, Alan. Algorithmic learning. Oxford: Clarendon Press, 1994.
Rao, Vemuri V., ed. Enhancing computer security with smart technology. Boca Raton, FL: Auerbach Publications, 2005.
Drescher, Gary L. Made-up minds: A constructivist approach to artificial intelligence. Cambridge, Mass: MIT Press, 1991.
Korb, Kevin B. Bayesian artificial intelligence. 2nd ed. Boca Raton, FL: CRC Press, 2011.
Bratko, Ivan. Prolog programming for artificial intelligence. Wokingham, England: Addison-Wesley, 1986.
Bratko, Ivan. Prolog programming for artificial intelligence. 3rd ed. Harlow, England: Addison Wesley, 2001.
Ivan, Bratko. Prolog programming for artificial intelligence. 2nd ed. Wokingham, England: Addison-Wesley Pub. Co., 1991.
Bratko, Ivan. Prolog programming for artificial intelligence. 4th ed. Harlow, England: Addison-Wesley, 2011.
Bratko, Ivan. Prolog programming for artificial intelligence. 2nd ed. Wokingham, England: Addison-Wesley Pub. Co., 1990.
Ivan, Bratko. Prolog programming for artificial intelligence. 2nd ed. Wokingham, England: Addison-Wesley Pub. Co, 1990.
Sutton, Richard S. Reinforcement learning: An introduction. Cambridge, Mass: MIT Press, 1998.
Tanimoto, S. The elements of artificial intelligence: An introduction using LISP. Rockville, MD: Computer Science Press, 1987.
Pollock, John L. Cognitive carpentry: A blueprint forhow to build a person. Cambridge, Mass: MIT Press, 1995.
Pollock, John L. Cognitive carpentry: A blueprint for how to build a person. Cambridge, Mass: MIT Press, 1995.
Russell, Stuart J. Artificial intelligence: A modern approach. 2nd ed. Upper Saddle River, N.J: Prentice Hall/Pearson Education, 2003.
Russell, Stuart J. Artificial intelligence: A modern approach. Englewood Cliffs, N.J: Prentice Hall, 1995.
Russell, Stuart J. Artificial intelligence: A modern approach. 2nd ed. Upper Saddle River, N.J: Prentice Hall, 2003.
Juliano, Benjoe A. Tracing chains-of-thought: Fuzzy methods in cognitive diagnosis. Heidelberg, [Germany]: Physica-Verlag, 1996.
1929-, Holland John H., ed. Induction: Processes of inference, learning, and discovery. Cambridge, Mass: MIT Press, 1986.
Gong, Shaogang. Dynamic vision: From images to face recognition. London: Imperial College Press, 2000.
Bareiss, Ray. Exemplar-based knowledge acquisition: A unified approach to concept representation, classification, and learning. Boston: Academic Press, 1989.
Borchardt, Gary C. Thinking between the lines: Computers and the comprehension of causaldescriptions. Cambridge, Mass: MIT Press, 1994.
Minsky, Marvin Lee. La societe de l'esprit. Paris: InterÉditions, 1988.
Borchardt, Gary C. Thinking between the lines: Computers and the comprehension of causal descriptions. Cambridge, Mass: MIT Press, 1994.
(Editor), Luc Lamontagne, and Mario Marchand (Editor), eds. Advances in Artificial Intelligence: 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Quebec City, ... (Lecture Notes in Computer Science). Springer, 2006.
Miclet, Laurent, Yves Kodratoff, Antoine Cornuéjols, and Tom Mitchell. Apprentissage artificiel : Concepts et algorithmes. Eyrolles, 2002.
Kanal, Laveen N., and Tod S. Levitt. Uncertainty in Artificial Intelligence 3 (Machine Intelligence and Pattern Recognition). North-Holland, 1989.
McClure, Nick. TensorFlow Machine Learning Cookbook: Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook. Packt Publishing - ebooks Account, 2017.
Bonnin, Rodolfo. Building Machine Learning Projects with TensorFlow. Packt Publishing, 2016.
Lapan, Maxim. Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more. Packt Publishing, 2018.
Mitra, Sushmita, Sujay Datta, Theodore Perkins, and George Michailidis. Introduction to Machine Learning and Bioinformatics. Taylor & Francis Group, 2019.
Mitra, Sushmita, Sujay Datta, Theodore Perkins, and George Michailidis. Introduction to Machine Learning and Bioinformatics. Taylor & Francis Group, 2008.
Mitra, Sushmita, Sujay Datta, Theodore Perkins, and George Michailidis. Introduction to Machine Learning and Bioinformatics. Taylor & Francis Group, 2008.
Mitra, Sushmita, Sujay Datta, Theodore Perkins, and George Michailidis. Introduction to Machine Learning and Bioinformatics. Chapman & Hall/CRC, 2008.
Machine Learning. McGraw-Hill Science/Engineering/Math, 1997.
Gaur, Loveleen, and K. C. Santosh. Artificial Intelligence and Machine Learning in Public Healthcare: Opportunities and Societal Impact. Springer Singapore Pte. Limited, 2021.