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Python machine learning : machine learning and deep learning with python, scikit-learn, and tensorflow 2 /
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. This new third edition is updated for Tenso...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited,
[2019]
|
| Edición: | Third edition |
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 003 | OCoLC | ||
| 005 | 20231027140348.0 | ||
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| 020 | |a 9781789958294 |q (electronic bk.) | ||
| 020 | |a 1789958296 |q (electronic bk.) | ||
| 020 | |a 9781789955750 |q (paperback) | ||
| 020 | |a 1789955750 |q (paperback) | ||
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| 082 | 0 | 4 | |a 005.133 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Raschka, Sebastian, |e author. | |
| 245 | 1 | 0 | |a Python machine learning : |b machine learning and deep learning with python, scikit-learn, and tensorflow 2 / |c Sebastian Raschka, Vahid Mirjalili |
| 250 | |a Third edition | ||
| 264 | 1 | |a Birmingham : |b Packt Publishing, Limited, |c [2019] | |
| 264 | 4 | |c Ã2019 | |
| 300 | |a 1 online resource (xxi, 741 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Includes index | ||
| 500 | |a "Third edition includes TensorFlow 2, GANS, and reinforcement learning"--Cover | ||
| 520 | |a Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. This new third edition is updated for TensorFlow 2 and the latest additions to ... | ||
| 505 | 0 | |a Giving computers the ability to learn from data -- Training simple machine learning algorithms for classification -- A tour of machine learning classifiers using scikit-learn -- Building good training sets-data preprocessing -- Compressing data via dimensionality reduction -- Learning best practices for model evaluation and hyperparmeter tuning -- Combining different models for ensemble learning -- Applying machine learning to sentiment analysis -- Embedding a machine learning model into a web application -- Predicting continuous target variables with regression analysis -- Working with unlabeled data-clustering analysis -- Implementing a multilayer artificial neural network from Scratch -- Parallelizing neural network training with TensorFlow -- Going deeper -- The mechanics of TensorFlow -- Classifying images with deep convolutional neural networks -- Modeling sequential data using recurrent neural networks -- Generative adversarial networks for synthesizing new data -- Reinforcement learning for decision making in complex environments | |
| 588 | 0 | |a Print version record | |
| 590 | |a Knovel |b ACADEMIC - General Engineering & Project Administration | ||
| 590 | |a Knovel |b ACADEMIC - Software Engineering | ||
| 650 | 0 | |a Python. | |
| 700 | 1 | |a Mirjalili, Vahid, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Raschka, Sebastian. |t Python machine learning. |b Third edition. |d Birmingham : Packt Publishing Ltd, 2019 |z 9781789955750 |w (OCoLC)1140369994 |
| 856 | 4 | 0 | |u https://appknovel.uam.elogim.com/kn/resources/kpPMLE0004/toc |z Texto completo |
| 938 | |a Askews and Holts Library Services |b ASKH |n AH37034579 | ||
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL6005547 | ||
| 994 | |a 92 |b IZTAP | ||