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| LEADER |
02680nam a22003017a 4500 |
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997626 |
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220603t20222022xxe ||| |||| 00| 0 eng d |
| 009 |
PPN262778475 |
| 020 |
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|a 9781801819312 (br.)
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| 020 |
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|a 1801819319
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| 020 |
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|z 9781801816380 (ebook)
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| 024 |
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|a 9781801819312
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| 041 |
0 |
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|a eng
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| 082 |
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|a 006.31
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| 100 |
1 |
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|a Raschka, Sebastian.
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| 245 |
1 |
0 |
|a Machine learning with PyTorch and Scikit-Learn :
|b develop machine learning and deep learning models with Python
|c Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili ; Dmytro Dzhulgakov.
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| 260 |
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|a Birmingham :
|b Packt Publishing.
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| 260 |
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|c C 2022.
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| 300 |
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|a 1 vol. (XXVIII-741 p.) :
|b ill. en noir, couv. en coul. ;
|c 24 cm.
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| 504 |
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|a Index
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| 505 |
0 |
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|a Chap. 1 : Giving computers the ability to learn from data -- Chap. 2 : Training simple machine learning algorithms for classification -- Chap. 3 : A tour of machine learning classifiers using Scikit-Learn -- Chap. 4 : Building good training datasets - Data preprocessing -- Chap. 5 : Compressing data via dimensionality reduction -- Chap. 6 : Learning best practices for model evaluation and hyperparameter tuning -- Chap. 7 : Combining different models for ensemble learning -- Chap. 8 : Applying machine learning to sentiment analysis -- Chap. 9 : Predicting continuous target variables with regression analysis -- Chap. 10 : Working with unlabeled data - Clustering analysis -- Chap. 11 : Implementing a multiplayer artificial neural network from scratch -- Chap. 12 : Parallelizing neural network training with PyTorch -- Chap. 13 : Going deeper - The mechanics of PyTorch -- Chap. 14 : Classifying images with deep convolutional neural networks -- Chap. 15 : Modeling sequential data using recurrent neural networks -- Chap. 16 : Transformers - Improving natural language processing with attention mechanisms -- Chap. 17 : Generative adversarial networks for synthesizing new data -- Chap. 18 : Graph neural networks for capturing dependencies in graph structured data -- Chap. 19 : Reinforcement learning for decision making in complex environments
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| 650 |
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|a Python (langage de programmation)
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| 650 |
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|a Apprentissage automatique
|x Logiciels
|
| 700 |
1 |
|
|a Liu, Yuxi (Hayden).
|4 aut
|
| 700 |
1 |
|
|a Mirjalili, Vahid.
|4 aut
|
| 700 |
1 |
|
|a Dzhulgakov, Dmytro.
|4 aui
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| 776 |
0 |
|
|0 282575685
|t Machine Learning with PyTorch and Scikit-Learn
|o develop machine learning and deep learning models with Python
|f Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili
|d 2022
|c Birmingham
|n Packt Publishing
|z 978-18-0181-638-0
|
| 997 |
|
|
|0 997626
|1 Livre papier
|a Ressource papier
|b INSA
|c 0/Bourges/
|c 1/Bourges/INSA CVL/
|z Bourges, INSA CVL, 006.31 RAS
|
