The Frontiers Of Machine Learning
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Deep Reinforcement Learning
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Author : Mohit Sewak
language : en
Publisher: Springer
Release Date : 2019-06-27
Deep Reinforcement Learning written by Mohit Sewak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-27 with Computers categories.
This book starts by presenting the basics of reinforcement learning using highly intuitive and easy-to-understand examples and applications, and then introduces the cutting-edge research advances that make reinforcement learning capable of out-performing most state-of-art systems, and even humans in a number of applications. The book not only equips readers with an understanding of multiple advanced and innovative algorithms, but also prepares them to implement systems such as those created by Google Deep Mind in actual code. This book is intended for readers who want to both understand and apply advanced concepts in a field that combines the best of two worlds – deep learning and reinforcement learning – to tap the potential of ‘advanced artificial intelligence’ for creating real-world applications and game-winning algorithms.
Machine Learning And Data Mining In Materials Science
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Author : Norbert Huber
language : en
Publisher: Frontiers Media SA
Release Date : 2020-04-22
Machine Learning And Data Mining In Materials Science written by Norbert Huber and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-22 with categories.
Large Scale Machine Learning In The Earth Sciences
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Author : Ashok N. Srivastava
language : en
Publisher: CRC Press
Release Date : 2017-08-01
Large Scale Machine Learning In The Earth Sciences written by Ashok N. Srivastava and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-01 with Computers categories.
From the Foreword: "While large-scale machine learning and data mining have greatly impacted a range of commercial applications, their use in the field of Earth sciences is still in the early stages. This book, edited by Ashok Srivastava, Ramakrishna Nemani, and Karsten Steinhaeuser, serves as an outstanding resource for anyone interested in the opportunities and challenges for the machine learning community in analyzing these data sets to answer questions of urgent societal interest...I hope that this book will inspire more computer scientists to focus on environmental applications, and Earth scientists to seek collaborations with researchers in machine learning and data mining to advance the frontiers in Earth sciences." --Vipin Kumar, University of Minnesota Large-Scale Machine Learning in the Earth Sciences provides researchers and practitioners with a broad overview of some of the key challenges in the intersection of Earth science, computer science, statistics, and related fields. It explores a wide range of topics and provides a compilation of recent research in the application of machine learning in the field of Earth Science. Making predictions based on observational data is a theme of the book, and the book includes chapters on the use of network science to understand and discover teleconnections in extreme climate and weather events, as well as using structured estimation in high dimensions. The use of ensemble machine learning models to combine predictions of global climate models using information from spatial and temporal patterns is also explored. The second part of the book features a discussion on statistical downscaling in climate with state-of-the-art scalable machine learning, as well as an overview of methods to understand and predict the proliferation of biological species due to changes in environmental conditions. The problem of using large-scale machine learning to study the formation of tornadoes is also explored in depth. The last part of the book covers the use of deep learning algorithms to classify images that have very high resolution, as well as the unmixing of spectral signals in remote sensing images of land cover. The authors also apply long-tail distributions to geoscience resources, in the final chapter of the book.
Machine Learning Concepts Tools And Data Visualization
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Author : Minsoo Kang
language : en
Publisher: World Scientific
Release Date : 2021-03-16
Machine Learning Concepts Tools And Data Visualization written by Minsoo Kang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-16 with Computers categories.
This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data science, and also includes case studies of well-known AI systems. The second is a step-by-step introduction to Azure Machine Learning, with examples provided. The third is an explanation of the techniques and methods used in data visualization with R, which can be used to communicate the results collected by the AI systems when they are analyzed statistically. Practice questions are provided throughout the book.
Knowledge Guided Machine Learning
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Author : Anuj Karpatne
language : en
Publisher: CRC Press
Release Date : 2022-08-15
Knowledge Guided Machine Learning written by Anuj Karpatne and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-15 with Business & Economics categories.
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML
The Frontiers Of Machine Learning
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Author : Royal Society (Great Britain)
language : en
Publisher:
Release Date : 2018
The Frontiers Of Machine Learning written by Royal Society (Great Britain) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Machine learning categories.
"The field of machine learning continues to advance at a rapid pace owing to increased computing power, better algorithms and tools, and greater availability of data. Machine learning is now being used in a range of applications, including transportation and developing automated vehicles, healthcare and understanding the genetic basis of disease, and criminal justice and predicting recidivism. As the technology advances, it promises additional applications that can contribute to individual and societal well-being. The Raymond and Beverly Sackler U.S.-U.K. Scientific Forum "The Frontiers off Machine Learning" took place on January 31 and February 1, 2017, at the Washington, D.C., headquarters of the National Academies of Sciences, Engineering, and Medicine. Participants included industry leaders, machine learning researchers, and experts in privacy and the law, and this report summarizes their high-level interdisciplinary discussions"--Publisher's description.
Machine Learning
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Author : Dr. Gowthami S
language : en
Publisher: RK Publication
Release Date : 2025-06-17
Machine Learning written by Dr. Gowthami S and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-17 with Computers categories.
This book offers a comprehensive introduction to Machine Learning, covering fundamental concepts, algorithms, and practical applications. Designed for students, researchers, and professionals, it explores supervised, unsupervised, and reinforcement learning with real-world use cases. Emphasis is placed on model evaluation, optimization, and ethical AI practices in modern data-driven environments.
Mastering Machine Learning
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date : 2023-09-05
Mastering Machine Learning written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-05 with Computers categories.
Are you ready to become a master of machine learning? In "Mastering Machine Learning" by Kris Hermans, you'll embark on a transformative journey that will empower you with the skills and knowledge needed to conquer the world of data-driven intelligence. Discover Cutting-Edge Techniques and Practical Applications From self-driving cars to personalized recommendations, machine learning is transforming industries and reshaping the way we live and work. In this comprehensive guide, Kris Hermans equips you with the tools to harness the power of machine learning. Dive into the core concepts, algorithms, and models that underpin this revolutionary field. Become a Proficient Practitioner Whether you're a beginner or an experienced professional, this book provides a clear and structured path to mastering machine learning. Through hands-on examples and real-world case studies, you'll gain practical expertise in implementing machine learning models and solving complex problems. Kris Hermans guides you through the process, ensuring you develop a deep understanding of the techniques and algorithms that drive intelligent systems. From Fundamentals to Advanced Topics "Mastering Machine Learning" covers the full spectrum of machine learning, starting with the foundations of supervised and unsupervised learning and progressing to reinforcement learning, neural networks, and deep learning. Explore diverse models and learn how to choose the right approach for different applications. With this knowledge, you'll be able to tackle real-world challenges with confidence. Unlock the Potential of Machine Learning Across Industries Discover how machine learning is revolutionizing industries such as finance, healthcare, e-commerce, and cybersecurity. Through captivating case studies, you'll witness the transformative impact of machine learning and gain insights into how organizations are leveraging this technology to drive innovation, improve decision-making, and achieve unprecedented success. Navigate Ethical Considerations As machine learning becomes increasingly powerful, it's crucial to consider the ethical implications. "Mastering Machine Learning" addresses these important considerations head-on. Learn about the ethical challenges and responsibilities associated with machine learning applications and gain the knowledge to make informed, ethical decisions in your own work.
The Ai Frontier
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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2024-11-08
The Ai Frontier written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-08 with Computers categories.
Step into the fascinating world of artificial intelligence with "The AI Frontier," an essential journey through the evolving landscape of machine learning. This compelling eBook invites you to explore cutting-edge technologies shaping our future, from foundational principles to tomorrow’s breakthroughs. Begin your adventure with a historical dive into the birth of machine learning, laying the groundwork with vital concepts such as algorithms, data, and the significant impact on everyday life. Venture deeper into the realm of neural networks, uncovering the intricate architectures and learning paradigms that enable machines to think like us. Immerse yourself in the revolutionary domain of deep learning with detailed explorations of convolutional, recurrent, and generative adversarial networks. Discover how these advancements are crafting unparalleled capabilities, including the remarkable transfer learning method. Unravel the complex mathematics that breathes life into these technologies. From the building blocks of linear algebra to the probabilistic methods that handle uncertainty, gain a solid understanding of how optimization techniques drive the quest for perfection. Get inspired by real-world applications that are transforming industries. Learn how machine learning is advancing health and medicine, creating autonomous systems, reshaping finance, and offering personalized experiences in entertainment. Address the crucial challenges that accompany these innovations. Examine the ethical implications, such as algorithmic bias and privacy concerns, and contemplate the societal impacts of automation on jobs and the future. Explore the ever-expanding toolkit of machine learning, spanning popular frameworks and programming languages to hardware considerations that power these advancements. Review insightful case studies of both triumphs and missteps, providing valuable lessons. Peer into the future, where emerging trends like quantum computing and AI push boundaries. "The AI Frontier" equips you to balance innovation with ethics and prepares you for continuous learning in this dynamic field. Embark on this enlightening journey, and explore the new possibilities that machine learning offers.
Algorithms Of Intelligence Exploring The World Of Machine Learning
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Author : Dr R. Keerthika
language : en
Publisher: Inkbound Publishers
Release Date : 2022-01-20
Algorithms Of Intelligence Exploring The World Of Machine Learning written by Dr R. Keerthika and has been published by Inkbound Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-20 with Computers categories.
Delve into the fascinating world of machine learning with this comprehensive guide, which unpacks the algorithms driving today's intelligent systems. From foundational concepts to advanced applications, this book is essential for anyone looking to understand the mechanics behind AI.