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020 _a9781484298015
_9978-1-4842-9801-5
024 7 _a10.1007/978-1-4842-9801-5
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
100 1 _aKashyap, Patanjali.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_966182
245 1 0 _aMachine Learning for Decision Makers
_h[electronic resource] :
_bCognitive Computing Fundamentals for Better Decision Making /
_cby Patanjali Kashyap.
250 _a2nd ed. 2024.
264 1 _aBerkeley, CA :
_bApress :
_bImprint: Apress,
_c2024.
300 _aXXI, 661 p. 45 illus., 13 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aChapter 1: Let’s Integrate with Machine Learning -- Chapter 2: The Practical Concepts of Machine Learning -- Chapter 3: Machine Learning Algorithms and Their Relationship with Modern Technologies -- Chapter 4: Technology Stack for Machine Learning and Associated Technologies -- Chapter 5: Industrial Applications of Machine Learning -- Chapter 6: I Am the Future: Machine Learning in Action -- Chapter 7: Innovation, KPIs, Best Practices, and More for Machine Learning -- Chapter 8: Do Not Forget Me: The Human Side of Machine Learning -- Chapter 9: Quantum Computers and Machine Learning -- Chapter 10: Let’s Wrap Up: The Final Destination.
520 _aThis new and updated edition takes you through the details of machine learning to give you an understanding of cognitive computing, IoT, big data, AI, quantum computing, and more. The book explains how machine learning techniques are used to solve fundamental and complex societal and industry problems. This second edition builds upon the foundation of the first book, revises all of the chapters, and updates the research, case studies, and practical examples to bring the book up to date with changes that have occurred in machine learning. A new chapter on quantum computers and machine learning is included to prepare you for future challenges. Insights for decision makers will help you understand machine learning and associated technologies and make efficient, reliable, smart, and efficient business decisions. All aspects of machine learning are covered, ranging from algorithms to industry applications. Wherever possible, required practical guidelines and best practices related to machine learning and associated technologies are discussed. Also covered in this edition are hot-button topics such as ChatGPT, superposition, quantum machine learning, and reinforcement learning from human feedback (RLHF) technology. Upon completing this book, you will understand machine learning, IoT, and cognitive computing and be prepared to cope with future challenges related to machine learning. You will: Learn the essentials of machine learning, AI, cloud, and the cognitive computing technology stack Understand business and enterprise decision-making using machine learning Become familiar with machine learning best practices Gain knowledge of quantum computing and quantum machine learning.
650 0 _aArtificial intelligence.
_958441
650 0 _aSoftware engineering.
_933953
650 0 _aAlgorithms.
_958677
650 1 4 _aArtificial Intelligence.
_958441
650 2 4 _aSoftware Engineering.
_933953
650 2 4 _aAlgorithms.
_958677
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9781484298008
776 0 8 _iPrinted edition:
_z9781484298022
776 0 8 _iPrinted edition:
_z9798868806872
856 4 0 _uhttps://doi.org/10.1007/978-1-4842-9801-5
912 _aZDB-2-CWD
912 _aZDB-2-SXPC
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