| Titre : |
Hands-on machine learning with Scikit-Learn, Keras and TensorFlow : concepts, tools, and techniques to build intelligent systems |
| Type de document : |
texte imprimé |
| Auteurs : |
Aurélien Géron, Auteur |
| Mention d'édition : |
2nd ed |
| Editeur : |
Sebastopol [Etats-Unis] : O'Reilly Media |
| Année de publication : |
2019 |
| Importance : |
XXV, 819 p. |
| Présentation : |
ill. |
| Format : |
24 cm |
| ISBN/ISSN/EAN : |
978-1-4920-3264-9 |
| Note générale : |
Appendix. Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Apprentissage automatique
Intelligence artificielle
Machine learning
Artificial intelligence |
| Index. décimale : |
004.8 Intelligence artificielle |
| Note de contenu : |
Summary :
Part I. The fundamentals of machine learning.
1. The machine learning landscape.
2. End-to-end machine learning project.
3. Classification.
4. Training models.
5. Support vector machine.
6. Decision trees.
7. Ensemble learning and random forests.
8. Dimensionality reduction.
9. Unsupervised Learning Techniques.
Part II.Neural networks and deep learning.
10.Introduction to Artificial Neural Networks with Keras.
11. Training Deep Neural Networks.
12. Custom Models and Training with TensorFlow.
13. Loading and Preprocessing Data with TensorFlow.
14. Deep Computer Vision Using Convolutional Neural Networks.
15. Processing Sequences Using RNNs and CNNs.
16. Natural Language Processing with RNNs and Attention.
17. Representation Learning and Generative Learning Using Autoencoders and GANs.
18.Reinforcement Learning.
19. Training and Deploying TensorFlow Models at Scale. |
Hands-on machine learning with Scikit-Learn, Keras and TensorFlow : concepts, tools, and techniques to build intelligent systems [texte imprimé] / Aurélien Géron, Auteur . - 2nd ed . - Sebastopol [Etats-Unis] : O'Reilly Media, 2019 . - XXV, 819 p. : ill. ; 24 cm. ISBN : 978-1-4920-3264-9 Appendix. Index Langues : Anglais ( eng)
| Mots-clés : |
Apprentissage automatique
Intelligence artificielle
Machine learning
Artificial intelligence |
| Index. décimale : |
004.8 Intelligence artificielle |
| Note de contenu : |
Summary :
Part I. The fundamentals of machine learning.
1. The machine learning landscape.
2. End-to-end machine learning project.
3. Classification.
4. Training models.
5. Support vector machine.
6. Decision trees.
7. Ensemble learning and random forests.
8. Dimensionality reduction.
9. Unsupervised Learning Techniques.
Part II.Neural networks and deep learning.
10.Introduction to Artificial Neural Networks with Keras.
11. Training Deep Neural Networks.
12. Custom Models and Training with TensorFlow.
13. Loading and Preprocessing Data with TensorFlow.
14. Deep Computer Vision Using Convolutional Neural Networks.
15. Processing Sequences Using RNNs and CNNs.
16. Natural Language Processing with RNNs and Attention.
17. Representation Learning and Generative Learning Using Autoencoders and GANs.
18.Reinforcement Learning.
19. Training and Deploying TensorFlow Models at Scale. |
|  |
Hands-on machine learning with Scikit-Learn, Keras and TensorFlow (2019)
