Machine Learning Foundations And Applications
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Handbook Of Research On Machine Learning
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Author : Monika Mangla
language : en
Publisher: CRC Press
Release Date : 2022-08-04
Handbook Of Research On Machine Learning written by Monika Mangla and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-04 with Computers categories.
This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.
Machine Learning Foundations And Applications
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Author : Jarrel E
language : en
Publisher:
Release Date : 2025-05-10
Machine Learning Foundations And Applications written by Jarrel E and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-10 with Computers categories.
Master the algorithms powering today's AI revolution. This practical guide breaks down the foundations of machine learning into clear, structured lessons-covering supervised learning, unsupervised learning, and reinforcement learning. Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work-mathematically and computationally. This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development. If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts-with clarity, depth, and purpose.
Machine Learning Foundations And Applications
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Author : Jarrel E
language : en
Publisher:
Release Date : 2025-05-09
Machine Learning Foundations And Applications written by Jarrel E and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-09 with Computers categories.
Master the algorithms powering today's AI revolution. This practical guide breaks down the foundations of machine learning into clear, structured lessons-covering supervised learning, unsupervised learning, and reinforcement learning. Whether you're a student, developer, or data professional, you'll learn how real-world models like linear regression, neural networks, support vector machines, PCA, and Q-learning actually work-mathematically and computationally. This book blends theory with implementation, offering step-by-step explanations, intuitive insights, and practical tools for applying machine learning in business, research, and product development. If you're serious about learning machine learning, this is the book that takes you from first principles to advanced concepts-with clarity, depth, and purpose.
Imbalanced Learning
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Author : Haibo He
language : en
Publisher: John Wiley & Sons
Release Date : 2013-06-07
Imbalanced Learning written by Haibo He 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 2013-06-07 with Technology & Engineering categories.
The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles, algorithms, and tools to transform vast amounts of raw data efficiently into information and knowledge representation. The first comprehensive look at this new branch of machine learning, this book offers a critical review of the problem of imbalanced learning, covering the state of the art in techniques, principles, and real-world applications. Featuring contributions from experts in both academia and industry, Imbalanced Learning: Foundations, Algorithms, and Applications provides chapter coverage on: Foundations of Imbalanced Learning Imbalanced Datasets: From Sampling to Classifiers Ensemble Methods for Class Imbalance Learning Class Imbalance Learning Methods for Support Vector Machines Class Imbalance and Active Learning Nonstationary Stream Data Learning with Imbalanced Class Distribution Assessment Metrics for Imbalanced Learning Imbalanced Learning: Foundations, Algorithms, and Applications will help scientists and engineers learn how to tackle the problem of learning from imbalanced datasets, and gain insight into current developments in the field as well as future research directions.
Reinforcement Learning Foundations And Applications
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Author : Mukesh Kumar, Vivek Bhardwaj, Karan Bajaj, Saurav Mallik, Mingqiang Wang
language : en
Publisher: Bentham Science Publishers
Release Date : 2025-11-28
Reinforcement Learning Foundations And Applications written by Mukesh Kumar, Vivek Bhardwaj, Karan Bajaj, Saurav Mallik, Mingqiang Wang and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-28 with Computers categories.
Reinforcement Learning: Foundations and Applications combines rigorous theory with real-world relevance to introduce readers to one of the most influential branches of modern Artificial Intelligence. Walking readers through the essential principles, algorithms, and techniques that define reinforcement learning (RL), the book highlights how RL enables intelligent systems to learn from interaction and optimize decision-making in domains such as robotics, autonomous control, game AI, finance, and healthcare. The book opens with foundational RL concepts, including Markov Decision Processes, dynamic programming, and the exploration–exploitation dilemma. It then progresses to advanced material covering policy gradient methods, actor–critic architectures, deep reinforcement learning models, and multi-agent systems. Dedicated application chapters demonstrate how RL drives adaptive control, sequential decision-making, and practical problem-solving—supported by case studies, diagrams, and algorithm pseudocode. Rich with examples, research insights, and implementation guidance, this book equips readers with both the conceptual understanding and applied perspective needed to master reinforcement learning. Key Features Blends foundational RL theory with practical, application-driven case studies. Explains both model-based and model-free reinforcement learning approaches. Covers cutting-edge methods including Deep Q-Networks, continuous control, and reward shaping. Presents clear diagrams, pseudocode, and implementation notes to support hands-on learning. Highlights current challenges, limitations, and emerging research directions in RL.
Calculus For Machine Learning
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Author : BIMAL. KUJUR
language : en
Publisher: Independently Published
Release Date : 2025-02-15
Calculus For Machine Learning written by BIMAL. KUJUR and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-15 with categories.
This book is designed to bridge the gap between the mathematical foundations of calculus and their practical applications in the rapidly evolving field of machine learning (ML). Whether you are a student, a researcher, or a practitioner, this book aims to provide you with a comprehensive understanding of how calculus underpins many of the algorithms and techniques that drive modern ML. The Intersection of Calculus and Machine Learning Machine learning has transformed the way we approach data, enabling us to build models that can learn from and make predictions on complex datasets. At the heart of many ML algorithms lies calculus, the branch of mathematics that deals with rates of change and accumulation. From optimizing loss functions to training neural networks, calculus provides the tools necessary to understand and improve these models. This book is structured to take you on a journey from the fundamental concepts of calculus to their advanced applications in ML. We begin with a review of essential calculus topics, ensuring that readers have a solid foundation. We then delve into more specialized areas, such as gradient descent, backpropagation, and optimization techniques, illustrating how these concepts are applied in real-world ML problems.
Machine Learning Foundations Methodologies And Applications
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Author :
language : en
Publisher:
Release Date :
Machine Learning Foundations Methodologies And Applications written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Linear Algebra For Machine Learning
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Author : BIMAL. KUJUR
language : en
Publisher: Independently Published
Release Date : 2025-02
Linear Algebra For Machine Learning written by BIMAL. KUJUR and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02 with Computers categories.
Machine learning is revolutionizing industries by enabling computers to learn from data and make intelligent decisions. At the heart of machine learning lies linear algebra - a fundamental mathematical framework that powers algorithms, optimizations, and data transformations. This book, Linear Algebra for Machine Learning: Foundations and Applications, aims to bridge the gap between theoretical concepts and practical applications by providing an intuitive understanding of linear algebra's role in machine learning models. This book is structured to cater to both beginners and experienced practitioners. It starts with foundational concepts of linear algebra, including vectors, matrices, and eigenvalues, before progressing to their applications in machine learning. Each includes theoretical explanations accompanied by hands-on coding demonstrations to reinforce learning through practical implementation. By the end of this book, readers will gain a solid grasp of how linear algebra is employed in machine learning algorithms such as Support Vector Machines, Neural Networks, and Principal Component Analysis. The combination of mathematical insights and code demonstrations will equip readers with the skills necessary to develop, optimize, and interpret machine learning models effectively. Whether you are a student, researcher, or professional, this book serves as a comprehensive guide to understanding and applying linear algebra in the field of machine learning.
Mastering Machine Learning And Deep Learning
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Author : Krishna Kant Singh
language : en
Publisher: Wiley
Release Date : 2024-06-18
Mastering Machine Learning And Deep Learning written by Krishna Kant Singh and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-18 with Computers categories.
Federated Learning
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Author : Rajkumar Buyya
language : en
Publisher: Morgan Kaufmann
Release Date : 2026-06-01
Federated Learning written by Rajkumar Buyya and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-06-01 with Computers categories.
Federated Learning: Foundations and Applications provides a comprehensive guide to the foundations, architectures, systems, security, privacy, and applications of federated learning. Federated Learning has become an increasingly important machine learning technique because it introduces local data analysis within clients and requires exchange of only model parameters between clients and servers. This book covers the fundamental concepts of Federated Learning, including machine learning, deep learning, centralized learning, and distributed learning processes. The book then progresses to coverage of the architectures, algorithms, and system models of Federated Learning, as well as security, privacy, and energy-efficiency techniques. Finally, the book presents various applications of Federated Learning through real-world case studies illustrating both centralized and decentralized Federated Learning.