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1

Brigitte, Grau, and Chevallet Jean-Pierre, eds. La recherche d'informations précises: Traitement automatique de la langue, apprentissage et connaissances pour les systèmes de question-réponse. Paris: Hermès science publications, 2008.

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2

The design and analysis of efficient learning algorithms. Cambridge, Mass: MIT Press, 1992.

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3

Support vector machines for pattern classification. 2nd ed. London: Springer, 2010.

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4

Marco, Colombetti, ed. Robot shaping: An experiment in behavior engineering. Cambridge, Mass: MIT Press, 1998.

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5

Bareiss, Ray. Exemplar-based knowledge acquisition: A unified approach to concept representation, classification, and learning. Boston: Academic Press, 1989.

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6

Bouchard, Gérard. Reconstitution automatique des familles: Le système SOREP. Chicoutimi: SOREP, Centre interuniversitaire de recherches sur les populations, 1985.

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7

Adriaans, Pieter. Data mining. Harlow, England: Addison-Wesley, 1996.

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8

Borchardt, Gary C. Thinking between the lines: Computers and the comprehension of causaldescriptions. Cambridge, Mass: MIT Press, 1994.

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9

Borchardt, Gary C. Thinking between the lines: Computers and the comprehension of causal descriptions. Cambridge, Mass: MIT Press, 1994.

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10

Silberztein, Max. Dictionnaires électroniques et analyse automatique de textes: Le système INTEX. Paris: Masson, 1993.

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11

Pollock, John L. Cognitive carpentry: A blueprint forhow to build a person. Cambridge, Mass: MIT Press, 1995.

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12

Cognitive carpentry: A blueprint for how to build a person. Cambridge, Mass: MIT Press, 1995.

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13

Robidas, Guy. Psychologie de l'apprentissage: Un système d'apprentissage-enseignement personnalisé. Brossard, Qué: Editions Behaviora, 1989.

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14

Xanthos, Aris. Apprentissage automatique de la morphologie: Le cas des structures racine-schème. Bern: Peter Lang, 2008.

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15

Agnès, Guillot, and Daucé Emmanuel, eds. Approche dynamique de la cognition artificielle. Paris: Hermès science publications, 2002.

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16

Alpaydin, Ethem. Introduction to machine learning. Cambridge, MA: MIT Press, 2005.

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17

Machine learning: The art and science of algorithms that make sense of data. Cambridge: Cambridge University Press, 2012.

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18

Elements of machine learning. San Francisco, Calif: Morgan Kaufmann, 1996.

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19

International Conference on Machine Learning (7th 1990 University of Texas). Machine learning: Proceedings of the seventh international conference (1990), University of Texas, Austin, Texas, June 21-23, 1990. Edited by Porter Bruce 1956-, Mooney Raymond J, and Artificial Intelligence and Robotics Program (U.S.). San Mateo, Calif: Morgan Kaufmann Publishers, 1990.

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20

Network anomaly detection: A machine learning perspective. Boca Raton: CRC Press, Taylor & Francis Group, 2014.

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21

Apprentissage symbolique: Une approche de l'intelligence artificielle. Toulouse (France): Cépaduès-éditions, 1993.

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22

Brazdil, Pavel B. Metalearning: Applications to data mining. Berlin: Springer, 2009.

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23

Oscar, Firschein, ed. Intelligence: The eye, the brain, and the computer. Reading, Mass: Addison-Wesley, 1987.

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24

ICML '02: 19th International Conference on Machine Learning. Morgan Kaufmann, 2002.

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25

Madala, H. R. Inductive Learning Algorithms for Complex Systems Modeling. Taylor & Francis Group, 2019.

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26

Madala, H. R. Inductive Learning Algorithms for Complex Systems Modeling. Taylor & Francis Group, 2019.

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27

Poongodi, T., Balamurugan Balusamy, Firoz Khan KP, and Bansal Himani. Machine Learning and Analytics in Healthcare Systems. Taylor & Francis Group, 2021.

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28

Suganthi, K., R. Karthik, G. Rajesh, and Peter Ho Chiung Ching. Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems. Taylor & Francis Group, 2021.

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29

Suganthi, K., R. Karthik, G. Rajesh, and Peter Ho Chiung Ching. Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems. Taylor & Francis Group, 2021.

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30

Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems. CRC Press, 2021.

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31

Bansal, Himani, T. Poongodi, and Balamurugan Balusamy. Machine Learning and Analytics in Healthcare Systems: Principles and Applications. CRC Press LLC, 2021.

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32

Machine Learning and Analytics in Healthcare Systems: Principles and Applications. Taylor & Francis Group, 2021.

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33

Bansal, Himani, T. Poongodi, Balamurugan Balusamy, and Firoz Khan KP. Machine Learning and Analytics in Healthcare Systems: Principles and Applications. Taylor & Francis Group, 2021.

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34

GIS and Machine Learning for Small Area Classifications in Developing Countries. Taylor & Francis Group, 2020.

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35

Traffic Information and Control. Institution of Engineering & Technology, 2021.

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36

He, Zhengbing, and Ruimin Li. Traffic Information and Control. Institution of Engineering & Technology, 2020.

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37

Ojo, Adegbola. GIS and Machine Learning for Small Area Classifications in Developing Countries. Taylor & Francis Group, 2020.

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38

Ojo, Adegbola. GIS and Machine Learning for Small Area Classifications in Developing Countries. Taylor & Francis Group, 2020.

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39

Ojo, Adegbola. GIS and Machine Learning for Small Area Classifications in Developing Countries. Taylor & Francis Group, 2020.

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40

Systems That Learn: An Introduction to Learning Theory for Cognitive and Computer Scientists (Learning, Development, and Conceptual Change). The MIT Press, 1990.

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41

Designing Machine Learning Systems with Python. Packt Publishing, 2016.

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42

Supervised and Unsupervised Ensemble Methods and Their Applications Studies in Computational Intelligence. Springer, 2008.

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43

Crane, Harry. Probabilistic Foundations of Statistical Network Analysis. Taylor & Francis Group, 2018.

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44

Crane, Harry. Probabilistic Foundations of Statistical Network Analysis. Taylor & Francis Group, 2018.

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45

Probabilistic Foundations of Statistical Network Analysis. Chapman and Hall/CRC, 2018.

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46

Kumar, Neeraj, and Aaisha Makkar. Machine Learning in Cognitive IoT. Taylor & Francis Group, 2020.

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47

Machine Learning in Cognitive Iot. Taylor & Francis Group, 2020.

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48

Kumar, Neeraj, and Aaisha Makkar. Machine Learning in Cognitive IoT. Taylor & Francis Group, 2020.

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49

Kumar, Neeraj, and Aaisha Makkar. Machine Learning in Cognitive IoT. Taylor & Francis Group, 2020.

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50

Bareiss, Ray. Exemplar Based Knowledge Acquisition: A Unified Approach to Concept Representation Classification, and Learning (Prspctvs in Art Intlgnce, Vol 2). Academic Pr, 1990.

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