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Practical deep learning : = a Python...

Kneusel, Ronald T.

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Practical deep learning : = a Python-based introduction /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Practical deep learning :/ by Ronald T. Kneusel.
Reminder of title:	a Python-based introduction /
Author:	Kneusel, Ronald T.
Published:	San Francisco, CA :No Starch Press, Inc., : c2021.,
Description:	xxx, 426 p. :ill. ;24 cm.
Notes:	Includes index.
[NT 15003449]:	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.
Subject:	Machine learning. -
ISBN:	9781718500747

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: 9781718500747US59.99

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 /
LDR:01523cam a2200241 a 4500 001 2339515
003 OCoLC
005 20210612052042.8
008 240612s2021 caua 001 0 eng
010 $a 2020035097
020 $a 9781718500747 $q (pbk.) : $c US59.99
020 $a 1718500742 $q (pbk.)
040 $a DLC $b eng $c DLC $d OCLCO $d OCLCF $d BDX $d YDX $d NDHU
041 0 # $a eng
042 $a pcc
050 0 0 $a Q325.5 $b .K55 2021
082 0 0 $a 006.3/1 $2 23
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.
250 $a 1st ed.
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.
650 # 0 $a Machine learning. $3 533906
650 # 0 $a Python (Computer program language) $3 729789