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LEADER 00000cam a2200481Ii 4500
003 OCoLC
005 20240129213017.0
006 m o d
007 cr un|---aucuu
008 220216s2022 mau o 001 0 eng d
020 9781119821908|q(electronic bk. : oBook)
020 1119821908|q(electronic bk. : oBook)
020 9781119821885|q(electronic bk.)
020 1119821886|q(electronic bk.)
024 7 10.1002/9781119821908|2doi
029 1 AU@|b000071250361
035 (OCoLC)1297039923
037 9781119821250|bO'Reilly Media
040 DG1|beng|erda|epn|cDG1|dOCLCO|dOCLCF|dORMDA|dUKAHL|dN$T
|dOCLCQ|dOCLCO
049 INap
082 04 006.3/1
082 04 006.3/1|223
099 eBook O'Reilly for Public Libraries
245 00 Fundamentals and methods of machine and deep learning :
|balgorithms, tools and applications /|cedited by Pradeep
Singh.|h[O'Reilly electronic resource]
264 1 Beverly, MA :|bScrivener Publishing ;|aHoboken, NJ :
|bWiley,|c2022.
300 1 online resource.
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
500 Includes index.
505 0 Front Matter -- Supervised Machine Learning: Algorithms
and Applications / Shruthi H Shetty, Sumiksha Shetty,
Chandra Singh, Ashwath Rao -- Zonotic Diseases Detection
Using Ensemble Machine Learning Algorithms / K Bhargavi --
Model Evaluation / Ravi Shekhar Tiwari -- Analysis of M-
SEIR and LSTM Models for the Prediction of COVID-19 Using
RMSLE / S Archith, C Yukta, HR Archana, HH Surendra -- The
Significance of Feature Selection Techniques in Machine
Learning / N Bharathi, BS Rishiikeshwer, T Aswin Shriram,
B Santhi, GR Brindha -- Use of Machine Learning and Deep
Learning in Healthcare-A Review on Disease Prediction
System / R Radha, R Gopalakrishnan -- Detection of
Diabetic Retinopathy Using Ensemble Learning Techniques /
Anirban Dutta, Parul Agarwal, Anushka Mittal, Shishir
Khandelwal, Shikha Mehta -- Machine Learning and Deep
Learning for Medical Analysis-A Case Study on Heart
Disease Data / AM Swetha, B Santhi, GR Brindha -- A Novel
Convolutional Neural Network Model to Predict Software
Defects / Kumar Rajnish, Vandana Bhattacharjee, Mansi
Gupta -- Predictive Analysis of Online Television Videos
Using Machine Learning Algorithms / Jeyavadhanam B Rebecca,
VV Ramalingam, V Sugumaran, D Rajkumar -- A Combinational
Deep Learning Approach to Visually Evoked EEG-Based Image
Classification / Nandini Kumari, Shamama Anwar, Vandana
Bhattacharjee -- Application of Machine Learning
Algorithms With Balancing Techniques for Credit Card Fraud
Detection: A Comparative Analysis / Shiksha -- Crack
Detection in Civil Structures Using Deep Learning /
Bijimalla Shiva Vamshi Krishna, BS Rishiikeshwer, J Sanjay
Raju, N Bharathi, C Venkatasubramanian, GR Brindha --
Measuring Urban Sprawl Using Machine Learning / Keerti
Kulkarni, P A Vijaya -- Application of Deep Learning
Algorithms in Medical Image Processing: A Survey / B
Santhi, AM Swetha, AM Ashutosh -- Simulation of Self-
Driving Cars Using Deep Learning / M K Rahul, Praveen L
Uppunda, Raju S Vinayaka, B Sumukh, C Gururaj -- Assistive
Technologies for Visual, Hearing, and Speech Impairments:
Machine Learning and Deep Learning Solutions / K C Shahira,
C J Sruthi, A Lijiya -- Case Studies: Deep Learning in
Remote Sensing / Jenifer A Emily, N Sudha -- Index
520 FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The
book provides a practical approach by explaining the
concepts of machine learning and deep learning algorithms,
evaluation of methodology advances, and algorithm
demonstrations with applications. Over the past two
decades, the field of machine learning and its subfield
deep learning have played a main role in software
applications development. Also, in recent research studies,
they are regarded as one of the disruptive technologies
that will transform our future life, business, and the
global economy. The recent explosion of digital data in a
wide variety of domains, including science, engineering,
Internet of Things, biomedical, healthcare, and many
business sectors, has declared the era of big data, which
cannot be analysed by classical statistics but by the more
modern, robust machine learning and deep learning
techniques. Since machine learning learns from data rather
than by programming hard-coded decision rules, an attempt
is being made to use machine learning to make computers
that are able to solve problems like human experts in the
field. The goal of this book is to present a??practical
approach by explaining the concepts of machine learning
and deep learning algorithms with applications. Supervised
machine learning algorithms, ensemble machine learning
algorithms, feature selection, deep learning techniques,
and their applications are discussed. Also included in the
eighteen chapters is unique information which provides a
clear understanding of concepts by using algorithms and
case studies illustrated with applications of machine
learning and deep learning in different domains, including
disease prediction, software defect prediction, online
television analysis, medical image processing, etc. Each
of the chapters briefly described below provides both a
chosen approach and its implementation. Audience
Researchers and engineers in artificial intelligence,
computer scientists as well as software developers.
588 0 Online resource; title from PDF title page (SpringerLink,
viewed February 16, 2022).
590 O'Reilly|bO'Reilly Online Learning: Academic/Public
Library Edition
650 0 Machine learning.
650 6 Apprentissage automatique.
650 7 Machine learning|2fast
700 1 Singh, Pradeep,|eeditor.
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
learning.oreilly.com/library/view/~/9781119821250/?ar
|zAvailable on O'Reilly for Public Libraries
938 Askews and Holts Library Services|bASKH|nAH39667026
938 Askews and Holts Library Services|bASKH|nAH39677289
938 EBSCOhost|bEBSC|n3159030
994 92|bJFN