國立虎尾科技大學 |

Essentials of deep learning and AI : = experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Essentials of deep learning and AI :/ Shashidhar Soppin, Manjunath Ramachandra, B N Chandrashekar.
其他題名:	experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn /
作者:	Soppin, Shashidhar.
其他作者:	Chandrashekar, B N,
面頁冊數:	1 online resource (395 pages)
標題:	COMPUTERS / Data Science / Machine Learning. -
電子資源:	https://portal.igpublish.com/iglibrary/search/BPB0000287.html
ISBN:	9789391030025

Essentials of deep learning and AI : = experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn /
Soppin, Shashidhar.

Essentials of deep learning and AI :experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn /Shashidhar Soppin, Manjunath Ramachandra, B N Chandrashekar. - 1 online resource (395 pages)

Includes bibliographical references and index.

Essentials of deep learning and AI : experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn -- Foreword -- Dedication -- About the Authors -- About the Reviewer -- Acknowledgement -- Preface -- Table of Contents -- Chapter 1: Introduction -- Chapter 2: Supervised Machine Learning -- Chapter 3: System Analysis with Machine Learning/ Un-Supervised Learning -- Chapter 4: Feature Engineering -- Chapter 5: Classification, Clustering, Association Rules, and Regression -- Chapter 6: Time Series Analysis -- Chapter 7: Data Cleanup, Characteristics and Feature Selection -- Chapter 8: Ensemble Model Development -- Chapter 9: Design with Deep Learning -- Chapter 10: Design with Multi Layered Perceptron (MLP) -- Chapter 11: Long Short Term Memory Networks -- Chapter 12: Autoencoders -- Chapter 13: Applications of Machine Learning and Deep Learning -- Chapter 14: Emerging and Future Technologies -- Index.

Access restricted to authorized users and institutions.

This book includes implemented code snippets and step-by-step instructions for how to use them. You'll be amazed at how SciKit-Learn, Keras, and TensorFlow are used in AI applications to speed up the learning process and produce superior results. With the help of detailed examples and code templates, you'll be running your scripts in no time. You will practice constructing models and optimise performance while working in an AI environment.

Mode of access: World Wide Web.

ISBN: 9789391030025Subjects--Topical Terms:

1483854
COMPUTERS / Data Science / Machine Learning.
Index Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: Q325.73

Dewey Class. No.: 006.3/1

Essentials of deep learning and AI : = experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn /
LDR:02542nam a2200289 i 4500 001 1157298
006 m eo d
007 cr cn |||m|||a
008 250717s2021 ob 000 0 eng d
020 $a 9789391030025
020 $a 9789391030353
035 $a BPB0000287
041 0 $a eng
050 0 0 $a Q325.73
082 0 0 $a 006.3/1
100 1 $a Soppin, Shashidhar. $3 1483877
245 1 0 $a Essentials of deep learning and AI : $b experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn / $c Shashidhar Soppin, Manjunath Ramachandra, B N Chandrashekar.
264 1 $a [Place of publication not identified] : $b BPB Publications, $c 2021.
264 4 $c ©2021
300 $a 1 online resource (395 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
504 $a Includes bibliographical references and index.
505 0 $a Essentials of deep learning and AI : experience unsupervised learning, autoencoders, feature engineering and time series analysis with tensorflow, keras, and scikit-learn -- Foreword -- Dedication -- About the Authors -- About the Reviewer -- Acknowledgement -- Preface -- Table of Contents -- Chapter 1: Introduction -- Chapter 2: Supervised Machine Learning -- Chapter 3: System Analysis with Machine Learning/ Un-Supervised Learning -- Chapter 4: Feature Engineering -- Chapter 5: Classification, Clustering, Association Rules, and Regression -- Chapter 6: Time Series Analysis -- Chapter 7: Data Cleanup, Characteristics and Feature Selection -- Chapter 8: Ensemble Model Development -- Chapter 9: Design with Deep Learning -- Chapter 10: Design with Multi Layered Perceptron (MLP) -- Chapter 11: Long Short Term Memory Networks -- Chapter 12: Autoencoders -- Chapter 13: Applications of Machine Learning and Deep Learning -- Chapter 14: Emerging and Future Technologies -- Index.
506 $a Access restricted to authorized users and institutions.
520 3 $a This book includes implemented code snippets and step-by-step instructions for how to use them. You'll be amazed at how SciKit-Learn, Keras, and TensorFlow are used in AI applications to speed up the learning process and produce superior results. With the help of detailed examples and code templates, you'll be running your scripts in no time. You will practice constructing models and optimise performance while working in an AI environment.
538 $a Mode of access: World Wide Web.
650 7 $a COMPUTERS / Data Science / Machine Learning. $2 bisacsh $3 1483854
650 7 $a COMPUTERS / Data Science / Neural Networks. $2 bisacsh $3 1483844
650 7 $a COMPUTERS / Artificial Intelligence / Natural Language Processing. $2 bisacsh $3 1483851
650 7 $a COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition. $2 bisacsh $3 1483850
655 4 $a Electronic books. $2 local $3 554714
700 1 $a Chandrashekar, B N, $e author $3 1483879
700 1 $a Ramachandra, Manjunath, $e author $3 1483878
856 4 0 $u https://portal.igpublish.com/iglibrary/search/BPB0000287.html