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Books on the topic 'Apprentissage profond – Réseaux neuronaux (informatique)'

Author: Grafiati

Published: 22 November 2023

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1

Rojas, Raúl. Neural networks: A systematic introduction. Berlin: Springer-Verlag, 1996.

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2

Thomas, Schiex, ed. Intelligence artificielle et informatique théorique. Toulouse: Cépaduès-éd., 1994.

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3

Søren, Brunak, ed. Bioinformatics: The machine learning approach. 2nd ed. Cambridge, Mass: MIT Press, 2001.

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4

E, Nicholson Ann, ed. Bayesian artificial intelligence. 2nd ed. Boca Raton, FL: CRC Press, 2011.

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5

Deep Learning: A Practitioner's Approach. O'Reilly Media, 2017.

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6

Korb, Kevin B., and Ann E. Nicholson. Bayesian Artificial Intelligence. Taylor & Francis Group, 2003.

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7

Bayesian Artificial Intelligence. Taylor & Francis Group, 2023.

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8

Applied Deep Learning and Computer Vision for Self-Driving Cars: Build Autonomous Vehicles Using Deep Neural Networks and Behavior-Cloning Techniques. Packt Publishing, Limited, 2020.

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9

Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms. O'Reilly Media, 2017.

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10

Bayesian Networks and Decision Graphs (Information Science and Statistics). Springer, 2007.

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11

Nielsen, Thomas D., and Finn V. Jensen. Bayesian Networks and Decision Graphs. Springer New York, 2010.

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12

Practical AI for Cybersecurity. Auerbach Publishers, Incorporated, 2021.

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13

Das, Ravi. Practical AI for Cybersecurity. Auerbach Publishers, Incorporated, 2021.

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14

Das, Ravi. Practical AI for Cybersecurity. Auerbach Publishers, Incorporated, 2021.

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15

R Deep Learning Cookbook: Solve complex neural net problems with TensorFlow, H2O and MXNet. Packt Publishing - ebooks Account, 2017.

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16

Nedjah, Nadia, Heitor Silverio Lopes, and Luiza De Macedo Mourelle. Evolutionary Multi-Objective System Design: Theory and Applications. Taylor & Francis Group, 2020.

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17

Nedjah, Nadia, Heitor Silverio Lopes, and Luiza De Macedo Mourelle. Evolutionary Multi-Objective System Design: Theory and Applications. Taylor & Francis Group, 2020.

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18

Nedjah, Nadia, Luiza de Macedo Mourelle, and Heitor Silvério Lopes. Evolutionary Multi-Objective System Design. Taylor & Francis Group, 2020.

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19

Evolutionary Multi-Objective System Design: Theory and Applications. Taylor & Francis Group, 2020.

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20

R Deep Learning Essentials: A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet, 2nd Edition. Packt Publishing, 2018.

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21

Cresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.

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22

Cresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2022.

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23

Cresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.

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24

Cresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.

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25

Cresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.

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26

Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.

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27

Abbott, L. F., and Peter Dayan. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. The MIT Press, 2005.

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28

Arslan, Hüseyin, and Ertuğrul Başar. Flexible and Cognitive Radio Access Technologies for 5G and Beyond. Institution of Engineering & Technology, 2020.

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29

Flexible and Cognitive Radio Access Technologies for 5G and Beyond. Institution of Engineering & Technology, 2020.

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