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020 _a9781119821908
_q(electronic bk. : oBook)
020 _a1119821908
_q(electronic bk. : oBook)
020 _a9781119821885
_q(electronic bk.)
020 _a1119821886
_q(electronic bk.)
020 _z9781119821250
024 7 _a10.1002/9781119821908
_2doi
029 1 _aAU@
_b000071250361
035 _a(OCoLC)1297039923
037 _a9781119821250
_bO'Reilly Media
050 4 _aQ325.5
082 0 4 _a006.3/1
_223
049 _aMAIN
245 0 0 _aFundamentals and methods of machine and deep learning :
_balgorithms, tools and applications /
_cedited by Pradeep Singh.
264 1 _aBeverly, MA :
_bScrivener Publishing ;
_aHoboken, NJ :
_bWiley,
_c2022.
300 _a1 online resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
505 0 _aFront 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
500 _aIncludes index.
588 0 _aOnline resource; title from PDF title page (SpringerLink, viewed February 16, 2022).
520 _aFUNDAMENTALS 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.
590 _aJohn Wiley and Sons
_bWiley Online Library: Complete oBooks
650 0 _aMachine learning.
650 6 _aApprentissage automatique.
650 7 _aMachine learning
_2fast
700 1 _aSingh, Pradeep,
_eeditor.
758 _ihas work:
_aFUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING (Text)
_1https://id.oclc.org/worldcat/entity/E39PCXY94Wthch7yrmBCtqbtGb
_4https://id.oclc.org/worldcat/ontology/hasWork
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119821908
938 _aAskews and Holts Library Services
_bASKH
_nAH39667026
938 _aAskews and Holts Library Services
_bASKH
_nAH39677289
938 _aEBSCOhost
_bEBSC
_n3159030
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