Libros sobre el tema "Apprentissage profond – Réseaux neuronaux (informatique)"
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Rojas, Raúl. Neural networks: A systematic introduction. Berlin: Springer-Verlag, 1996.
Buscar texto completoThomas, Schiex, ed. Intelligence artificielle et informatique théorique. Toulouse: Cépaduès-éd., 1994.
Buscar texto completoSøren, Brunak, ed. Bioinformatics: The machine learning approach. 2a ed. Cambridge, Mass: MIT Press, 2001.
Buscar texto completoE, Nicholson Ann, ed. Bayesian artificial intelligence. 2a ed. Boca Raton, FL: CRC Press, 2011.
Buscar texto completoDeep Learning: A Practitioner's Approach. O'Reilly Media, 2017.
Buscar texto completoKorb, Kevin B. y Ann E. Nicholson. Bayesian Artificial Intelligence. Taylor & Francis Group, 2003.
Buscar texto completoBayesian Artificial Intelligence. Taylor & Francis Group, 2023.
Buscar texto completoApplied Deep Learning and Computer Vision for Self-Driving Cars: Build Autonomous Vehicles Using Deep Neural Networks and Behavior-Cloning Techniques. Packt Publishing, Limited, 2020.
Buscar texto completoFundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms. O'Reilly Media, 2017.
Buscar texto completoBayesian Networks and Decision Graphs (Information Science and Statistics). Springer, 2007.
Buscar texto completoNielsen, Thomas D. y Finn V. Jensen. Bayesian Networks and Decision Graphs. Springer New York, 2010.
Buscar texto completoPractical AI for Cybersecurity. Auerbach Publishers, Incorporated, 2021.
Buscar texto completoDas, Ravi. Practical AI for Cybersecurity. Auerbach Publishers, Incorporated, 2021.
Buscar texto completoDas, Ravi. Practical AI for Cybersecurity. Auerbach Publishers, Incorporated, 2021.
Buscar texto completoR Deep Learning Cookbook: Solve complex neural net problems with TensorFlow, H2O and MXNet. Packt Publishing - ebooks Account, 2017.
Buscar texto completoNedjah, Nadia, Heitor Silverio Lopes y Luiza De Macedo Mourelle. Evolutionary Multi-Objective System Design: Theory and Applications. Taylor & Francis Group, 2020.
Buscar texto completoNedjah, Nadia, Heitor Silverio Lopes y Luiza De Macedo Mourelle. Evolutionary Multi-Objective System Design: Theory and Applications. Taylor & Francis Group, 2020.
Buscar texto completoNedjah, Nadia, Luiza de Macedo Mourelle y Heitor Silvério Lopes. Evolutionary Multi-Objective System Design. Taylor & Francis Group, 2020.
Buscar texto completoEvolutionary Multi-Objective System Design: Theory and Applications. Taylor & Francis Group, 2020.
Buscar texto completoR Deep Learning Essentials: A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet, 2nd Edition. Packt Publishing, 2018.
Buscar texto completoCresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.
Buscar texto completoCresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2022.
Buscar texto completoCresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.
Buscar texto completoCresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.
Buscar texto completoCresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.
Buscar texto completoCresson, Rémi. Deep Learning for Remote Sensing Images with Open Source Software. Taylor & Francis Group, 2020.
Buscar texto completoAbbott, L. F. y Peter Dayan. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. The MIT Press, 2005.
Buscar texto completoArslan, Hüseyin y Ertuğrul Başar. Flexible and Cognitive Radio Access Technologies for 5G and Beyond. Institution of Engineering & Technology, 2020.
Buscar texto completoArslan, Hüseyin y Ertuğrul Başar. Flexible and Cognitive Radio Access Technologies for 5G and Beyond. Institution of Engineering & Technology, 2020.
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