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Bayesian Reasoning and Gaussian Processes for Machine Learning Applications - Hardcover

 
9780367758479: Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

Synopsis

This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed by Gaussian process introduction, classification, regression, covariance, and performance analysis of Gaussian processes with other models.

FEATURES

  • Contains recent advancements in machine learning
  • Highlights applications of machine learning algorithms
  • Offers both quantitative and qualitative research
  • Includes numerous case studies

This book is aimed at graduates, researchers, and professionals in the field of data science and machine learning.

"synopsis" may belong to another edition of this title.

About the Author

Dr. Hemachandran K is working as a Professor – Artificial Intelligence at School of Business, Woxsen University, Hyderabad, Telangana, India. He is a passionate teacher with 14 years of teaching experience and 5 years of research experience. He is a strong educational professional with scientific bent of mind & is highly skilled in AI & ML. After receiving Ph.D. in embedded system at Dr. MGR Educational & Research Institute, India. He started doing inter disciplinary research in AI. He is an open-ended positive person who has a stupendous peer reviewed publication records in more than 20 journals and international conference publications. He served as an effective resource person at various national and international scientific conferences. He has a rich research experience in mentoring UG & PG student projects. He owes two patents to his credentials. He has life membership in estimeed professional bodies. He is one of the pioneers in establishing Single Board Computer lab at Ashoka Institutions, Hyderabad, India. His self-paced learning schedule and quench to upgrade and update his learning skills resulted in awarding around 15 online certificate courses conferred by COURSERA and other online platforms. His editorial skills earned him a position as an editorial board member in numerous reputed SCOPUS / SCI journals.

Dr. Preetha Mary George, an accomplished academician with over 14 years of experience in teaching and 5 years in research. Currently, works as an Associate Professor in the Department of Physics, Dr. M.G.R Educational & Research Institute University. Her research was focussed on topics Ultrasonics, water quality monitoring systems. She earned Ph.D. degree from Dr. M.G.R Educational and research Institute, Chennai, Tamilnadu in ‘ Acoustical Studies on Industrially Important Biomolecules'. She was recipient of MGR research award in 2016, and was recognized with special recognition award in 2017. For her most recent tenure in research, she had nourished her passion to publish around 2 Scopus indexed journals. She has recently published a patent in water monitoring systems. Her zeal towards interdisciplinary research abetted her to bridge science to technology. Her public relation, communication and interpersonal skills are commendable. She has got life time membership in various professional bodies.

Dr. Shubham Tayal is working as an Assistant Professor in the Department of Electronics and Communication Engineering at SR University, Warangal, Telangana, India. He has more than 6 Years of academic/research experience of teaching at the UG and PG levels. He has received his Ph.D. in Microelectronics & VLSI Design from the National Institute of Technology, Kurukshetra, M.Tech (VLSI Design) from YMCA University of Science and Technology, Faridabad, and B.Tech (Electronics and Communication Engineering) from MDU, Rohtak. He has published more than 25 research papers in various international journals and conferences of repute and many papers are under review. He is on the editorial and reviewer panel of many SCI/SCOPUS indexed international journals and conferences. Currently, he is the editor (or co-editor) for 06 books from CRC Press (Taylor & Francis Group, USA). He acted as the keynote speaker and delivered professional talks on various forums. He is a member of various professional bodies like IEEE, IRED, etc. He is on the advisory panel of many international conferences. He is a recipient of the Green ThinkerZ International Distinguished Young Researcher Award 2020. His research interests include simulation and modeling of Multi-gate semiconductor devices, Device-Circuit co-design in digital/analog domain, machine learning, and IoT.

Dr. Parveen Singla is Professor in Electronics & Communication Engineering Department of Chandigarh Engineering College- Chandigarh Group of Colleges, Landran, Mohali, Punjab. He did Bachelor of Engineering in Electronics & Communication Engineering with honors from Maharishi Dayanand University, Rohtak, Master in Technology in Electronics & Communication Engineering with honors from Kurukshetra University, Kurukshetra & PhD in Communication Systems from IKG Punjab Technical University, Jalandhar, India. He has 17 years of experience in the field of teaching and research. He has published more than 35 papers in various reputed journals, national and international conferences. He also organised more than 30 technical events for the students in order to enhance their technical skills and received Best International Technical Event Organiser Award. He is the guest editor of various reputed journals. His interest area includes Drone technology, Wireless Networks, Smart Antenna & Soft Computing.

Dr. Utku Kose received the B.S. degree in 2008 from computer education of Gazi University, Turkey as a faculty valedictorian. He received M.S. degree in 2010 from Afyon Kocatepe University, Turkey in the field of computer and D.S. / Ph. D. degree in 2017 from Selcuk University, Turkey in the field of computer engineering. Between 2009 and 2011, he has worked as a Research Assistant in Afyon Kocatepe University. Following, he has also worked as a Lecturer and Vocational School - Vice Director in Afyon Kocatepe University between 2011 and 2012, as a Lecturer and Research Center Director in Usak University between 2012 and 2017, and as an Assistant Professor in Suleyman Demirel University between 2017 and 2019. Currently, he is an Associate Professor in Suleyman Demirel University, Turkey. He has more than 100 publications including articles, authored and edited books, proceedings, and reports. He is also in editorial boards of many scientific journals and serves as one of the editors of the Biomedical and Robotics Healthcare book series by CRC Press. His research interest includes artificial intelligence, machine ethics, artificial intelligence safety, biomedical applications, optimization, the chaos theory, distance education, e-learning, computer education, and computer science.

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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed by Gaussian process introduction, classification, regression, covariance, and performance analysis of Gaussian processes with other models.FEATURES Contains recent advancements in machine learningHighlights applications of machine learning algorithmsOffers both quantitative and qualitative researchIncludes numerous case studiesThis book is aimed at graduates, researchers, and professionals in the field of data science and machine learning. 133 pp. Englisch. Seller Inventory # 9780367758479

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