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Practical deep learning : = a Python...

Kneusel, Ronald T.

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Practical deep learning : = a Python-based introduction /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Practical deep learning :/ by Ronald T. Kneusel.
其他題名:	a Python-based introduction /
作者:	Kneusel, Ronald T.
出版者:	San Francisco, CA :No Starch Press, Inc., : c2021.,
面頁冊數:	xxx, 426 p. :ill. ;24 cm.
附註:	Includes index.
內容註:	Foreword -- Acknowledgments -- Introduction -- 1. Getting started -- 2. Using Python -- 3. Using NumPy -- 4. Working with data -- 5. Building datasets -- 6. Classical machine learning -- 7. Experiments with classical models -- 8. Introduction to neural networks -- 9. Training a neural network -- 10. Experiments with neural networks -- 11. Evaluating models -- 12. Introduction to convolutional neural networks -- 13. Experiments with Keras and MNIST -- 14. Experiments with CIFAR-10 -- 15. A case study: classifying audio samples -- 16. Going further -- Index.
標題:	Machine learning. -
ISBN:	9781718500747 (pbk.) :

Practical deep learning : = a Python-based introduction /
Kneusel, Ronald T.

Practical deep learning :a Python-based introduction /by Ronald T. Kneusel. - 1st ed. - San Francisco, CA :No Starch Press, Inc.,c2021. - xxx, 426 p. :ill. ;24 cm.

Includes index.

Foreword -- Acknowledgments -- Introduction -- 1. Getting started -- 2. Using Python -- 3. Using NumPy -- 4. Working with data -- 5. Building datasets -- 6. Classical machine learning -- 7. Experiments with classical models -- 8. Introduction to neural networks -- 9. Training a neural network -- 10. Experiments with neural networks -- 11. Evaluating models -- 12. Introduction to convolutional neural networks -- 13. Experiments with Keras and MNIST -- 14. Experiments with CIFAR-10 -- 15. A case study: classifying audio samples -- 16. Going further -- Index.

"An introduction to machine learning and deep learning for beginners. Covers fundamental concepts before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Includes hands-on Python experiments for each model"--

ISBN: 9781718500747 (pbk.) :US59.99

LCCN: 2020035097Subjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .K55 2021

Dewey Class. No.: 006.3/1

Practical deep learning : = a Python-based introduction /
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100 1 $a Kneusel, Ronald T. $3 2145339
245 1 0 $a Practical deep learning : $b a Python-based introduction / $c by Ronald T. Kneusel.
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260 $a San Francisco, CA : $b No Starch Press, Inc., $c c2021.
300 $a xxx, 426 p. : $b ill. ; $c 24 cm.
500 $a Includes index.
505 0 $a Foreword -- Acknowledgments -- Introduction -- 1. Getting started -- 2. Using Python -- 3. Using NumPy -- 4. Working with data -- 5. Building datasets -- 6. Classical machine learning -- 7. Experiments with classical models -- 8. Introduction to neural networks -- 9. Training a neural network -- 10. Experiments with neural networks -- 11. Evaluating models -- 12. Introduction to convolutional neural networks -- 13. Experiments with Keras and MNIST -- 14. Experiments with CIFAR-10 -- 15. A case study: classifying audio samples -- 16. Going further -- Index.
520 $a "An introduction to machine learning and deep learning for beginners. Covers fundamental concepts before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Includes hands-on Python experiments for each model"-- $c Provided by publisher.
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650 0 $a Python (Computer program language) $3 729789