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Author: Raffaele Argiento
Publisher: Springer Nature
ISBN: 3030306119
Category : Mathematics
Languages : en
Pages : 184
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Book Description
This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.
Author: Raffaele Argiento
Publisher: Springer Nature
ISBN: 3030306119
Category : Mathematics
Languages : en
Pages : 184
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Book Description
This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.
Author: Olivier Pietquin
Publisher: Presses univ. de Louvain
ISBN: 2930344636
Category : Computers
Languages : en
Pages : 247
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Book Description
This book addresses the problems of spoken dialogue system design and especially automatic learning of optimal strategies for man-machine dialogues. Besides the description of the learning methods, this text proposes a framework for realistic simulation of human-machine dialogues based on probabilistic techniques, which allows automatic evaluation and unsupervised learning of dialogue strategies. This framework relies on stochastic modelling of modules composing spoken dialogue systems as well as on user modelling. Special care has been taken to build models that can either be hand-tuned or learned from generic data.
Author: Dr.Kongara Srinivasa Rao
Publisher: Leilani Katie Publication
ISBN: 9363484823
Category : Computers
Languages : en
Pages : 219
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Book Description
Dr.Kongara Srinivasa Rao, Assistant Professor, Department of Computer Science and Engineering, Faculty of Science and Technology (ICFAI Tech), ICFAI Foundation for Higher Education (IFHE), Hyderabad, Telangana, India. Dr.K.Sreeramamurthy, Professor, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad, Telangana, India. Dr.Yaswanth Kumar Alapati, Associate Professor, Department of Information Technology, R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 716
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Book Description
Author: Manfred Fahle
Publisher: MIT Press
ISBN: 9780262062213
Category : Medical
Languages : en
Pages : 484
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Book Description
Perceptual learning is the specific and relatively permanent modification of perception and behaviour following sensory experience. This book presents advances made during the 1990s in this rapidly growing field.
Author: CFA Institute
Publisher: John Wiley & Sons
ISBN: 1119743680
Category : Business & Economics
Languages : en
Pages : 288
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Book Description
The thoroughly revised and updated fourth edition of the companion workbook to Quantitative Investment Analysis is here. Now in its fourth edition, the Quantitative Investment Analysis Workbook offers a range of practical information and exercises that will facilitate your mastery of quantitative methods and their application in today's investment process. Part of the reputable CFA Institute Investment Series, the workbook is designed to further your hands-on experience with a variety of learning outcomes, summary overview sections, and challenging problems and solutions. The workbook provides all the statistical tools and latest information to help you become a confident and knowledgeable investor, including expanded problems on Machine Learning algorithms and the role of Big Data in investment contexts. Well suited for motivated individuals who learn on their own, as well as a general reference, this companion resource delivers a clear, example-driven method for practicing the tools and techniques covered in the primary Quantitative Investment Analysis, 4th Edition text.?? Inside you'll find information and exercises to help you: Work real-world problems associated with the modern quantitative investment process Master visualizing and summarizing data Review the fundamentals of single linear and multiple linear regression Use multifactor models Measure and manage market risk effectively In both the workbook and the primary Quantitative Investment Analysis, 4th Edition text, the authors go to great lengths to ensure an even treatment of subject matter, consistency of mathematical notation, and continuity of topic coverage that is critical to the learning process. For everyone who requires a streamlined route to mastering quantitative methods in investments, Quantitative Investment Analysis Workbook, 4th Edition offers world-class practice based on actual scenarios faced by professionals every day.
Author: Andrea Mechelli
Publisher: Academic Press
ISBN: 0128157402
Category : Medical
Languages : en
Pages : 412
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Book Description
Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians are using machine learning methods to develop and validate tools for assisting the diagnosis and treatment of patients with brain disorders. Machine Learning: Methods and Applications to Brain Disorders provides an up-to-date overview of how these methods can be applied to brain disorders, including both psychiatric and neurological disease. This book is written for a non-technical audience, such as neuroscientists, psychologists, psychiatrists, neurologists and health care practitioners. - Provides a non-technical introduction to machine learning and applications to brain disorders - Includes a detailed description of the most commonly used machine learning algorithms as well as some novel and promising approaches - Covers the main methodological challenges in the application of machine learning to brain disorders - Provides a step-by-step tutorial for implementing a machine learning pipeline to neuroimaging data in Python
Author: Pramod Gupta
Publisher: Springer Nature
ISBN: 3031591704
Category :
Languages : en
Pages : 509
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Book Description
Author: Seyedeh Leili Mirtaheri
Publisher: CRC Press
ISBN: 1000737691
Category : Business & Economics
Languages : en
Pages : 212
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Book Description
The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms. In summary, this book provides a comprehensive technological path from fundamental theories to the categorization of existing algorithms, covers state-of-the-art, practical evaluation tools and methods to empower you to use synthetic data to improve the performance of applications.
Author: Jiuquan Zhang
Publisher: Frontiers Media SA
ISBN: 2889747441
Category : Medical
Languages : en
Pages : 471
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Book Description
