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Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems
"Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how...
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| Auteur principal : | |
|---|---|
| Format : | Livre |
| Langue : | anglais |
| Titre complet : | Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems / Aurélien Géron |
| Publié : |
Sebastopol (Calif.) [etc.] :
O'Reilly
, copyright 2017 |
| Description matérielle : | 1 vol. (xx-551 p.) |
| Sujets : | |
| Documents associés : | Autre format:
Hands-on machine learning with Scikit-Learn and TensorFlow |
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| 200 | 1 | |a Hands-on machine learning with Scikit-Learn and TensorFlow |e concepts, tools, and techniques to build intelligent systems |f Aurélien Géron | |
| 210 | |a Sebastopol (Calif.) [etc.] |c O'Reilly |d copyright 2017 | ||
| 215 | |a 1 vol. (xx-551 p.) |c ill., couv. ill. |d 24 cm | ||
| 320 | |a Notes bibliogr. Index | ||
| 330 | |a "Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how." [source : 4ème de couv.] | ||
| 359 | 2 | |b The fundamentals of machine learning |c The machine learning landscape |c End-to-end machine learning project |c Classification |c Training models |c Support vector machines |c Decision trees |c Ensemble learning and random forests |c Dimensionality reduction |b Neural networks and deep learning |c Up and running with TensorFlow |c Introduction to artificial neural networks |c Training deep neural nets |c Distributing TensorFlow across devices and servers |c Convolutional neural networks |c Recurrent neural networks |c Autoencoders |c Reinforcement learning |b Exercise solutions |b Machine learning project checklist |b SVM dual problem |b Autodiff |b Other popular ANN architectures | |
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