New Advances In Machine Learning
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New Advances In Machine Learning
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Author : Yagang Zhang
language : en
Publisher: BoD – Books on Demand
Release Date : 2010-02-01
New Advances In Machine Learning written by Yagang Zhang and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-01 with Games & Activities categories.
The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call “learning” tasks, as we use the word in daily life. It is also broad enough to encompass computers that improve from experience in quite straightforward ways. The book will be of interest to industrial engineers and scientists as well as academics who wish to pursue machine learning. The book is intended for both graduate and postgraduate students in fields such as computer science, cybernetics, system sciences, engineering, statistics, and social sciences, and as a reference for software professionals and practitioners. The wide scope of the book provides a good introduction to many approaches of machine learning, and it is also the source of useful bibliographical information.
Advances In Machine Learning And Data Science
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Author : Damodar Reddy Edla
language : en
Publisher: Springer
Release Date : 2018-05-16
Advances In Machine Learning And Data Science written by Damodar Reddy Edla and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-16 with Technology & Engineering categories.
The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.
Empowering Artificial Intelligence Through Machine Learning
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Author : Nedunchezhian Raju
language : en
Publisher: CRC Press
Release Date : 2022-06-16
Empowering Artificial Intelligence Through Machine Learning written by Nedunchezhian Raju and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-16 with Computers categories.
This new volume, Empowering Artificial intelligence Through Machine Learning: New Advances and Applications, discusses various new applications of machine learning, a subset of the field of artificial intelligence. Artificial intelligence is considered to be the next-big-game changer in research and technology, The volume looks at how computing has enabled machines to learn, making machine and tools become smarter in many sectors, including science and engineering, healthcare, finance, education, gaming, security, and even agriculture, plus many more areas. Topics include techniques and methods in artificial intelligence for making machines intelligent, machine learning in healthcare, using machine learning for credit card fraud detection, using artificial intelligence in education using gaming and automatization with courses and outcomes mapping, and much more. The book will be valuable to professionals, faculty, and students in electronics and communication engineering, telecommunication engineering, network engineering, computer science and information technology.
Advances In Deep Learning
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Author : M. Arif Wani
language : en
Publisher: Springer
Release Date : 2019-03-14
Advances In Deep Learning written by M. Arif Wani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-14 with Technology & Engineering categories.
This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models.
Machine Learning Paradigms
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Author : George A. Tsihrintzis
language : en
Publisher: Springer
Release Date : 2021-07-25
Machine Learning Paradigms written by George A. Tsihrintzis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-25 with Computers categories.
At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance. This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest.
Advances In Machine Learning Applications In Software Engineering
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Author : Zhang, Du
language : en
Publisher: IGI Global
Release Date : 2006-10-31
Advances In Machine Learning Applications In Software Engineering written by Zhang, Du and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-10-31 with Computers categories.
"This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality while offering readers suggestions by proposing future work in this emerging research field"--Provided by publisher.
Advances In Financial Machine Learning
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Author : Marcos Lopez de Prado
language : en
Publisher: John Wiley & Sons
Release Date : 2018-01-23
Advances In Financial Machine Learning written by Marcos Lopez de Prado and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-23 with Business & Economics categories.
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Probabilistic Machine Learning
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Author : Kevin P. Murphy
language : en
Publisher: MIT Press
Release Date : 2022-03-01
Probabilistic Machine Learning written by Kevin P. Murphy and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Computers categories.
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Advances In Deep Learning Applications For Smart Cities
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Author : Kumar, Rajeev
language : en
Publisher: IGI Global
Release Date : 2022-05-13
Advances In Deep Learning Applications For Smart Cities written by Kumar, Rajeev and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-13 with Political Science categories.
Within the past decade, technology has grown exponentially, and governments have promoted smart cities. Emerging smart cities have become both crucibles and showrooms for the practical application of the internet of things (IoT), cloud computing, and the integration of big data into everyday life. This complex concoction requires new thinking of the synergistic utilization of deep learning and blockchain methods and data-driven decision making with automation infrastructure, autonomous transportation, and more. Advances in Deep Learning Applications for Smart Cities provides a global perspective on current and future trends concerning the integration of deep learning and blockchain for smart cities. It provides valuable insights on the best practices and success factors for smart cities. Covering topics such as digital healthcare, object detection methods, and power consumption, this book is an excellent reference for researchers, scientists, libraries, industry experts, government organizations, students and educators of higher education, business professionals, communication and marketing agencies, entrepreneurs, and academicians.
Machine Learning
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Author : Ryan Turner
language : en
Publisher: Publishing Factory
Release Date : 2020-04-19
Machine Learning written by Ryan Turner and has been published by Publishing Factory this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-19 with Computers categories.
Are you someone who is interested in how the next generation of machines can help you? Is Artificial Intelligence something to be feared, or do you imagine it that it will change our lives for the better? This book will provide the answers you need. Life is becoming ever more complex as we struggle to keep up with technology and use it to our best advantage. It is also more hectic and less certain, even in some of the mundane aspects of our lives, so that we are constantly trying to keep pace. New advancements in technology are paving the way to making life easier for billions and now things like Machine Learning and AI are changing the way we live. In this book, Machine Learning: The Ultimate Beginner’s Guide to Learn Machine Learning, Artificial Intelligence & Neural Networks Step by Step, you will see how this new technology continuously improves itself, can identify trends and patterns with ease and handles a wide variety of data, with chapters that explore: • Teaching the basic principles of Machine Learning • Why it is important and the many benefits that it provides • How Machine Learning differs from conventional programming • The fundamentals of algorithms • Challenges with Machine Learning and how you can easily overcome them • How it is going to change the future and make life easier • And much more… Machine Learning and AI are more than just science fiction. They are here now and undoubtedly will remain, improving and enhancing our lives in many ways, from the everyday to the vitally important. This book provides a platform that will give you a comprehensive understanding, that is second to none, of machine learning and its place in the world today. Get a copy now and see how Machine Learning will change your life!