Exploring Machine Learning Theory Practice And Innovations
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Exploring Machine Learning Theory Practice And Innovations
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Author : Dr. Vanitha Kakollu
language : en
Publisher: Academic Guru Publishing House
Release Date : 2024-12-23
Exploring Machine Learning Theory Practice And Innovations written by Dr. Vanitha Kakollu and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-23 with Study Aids categories.
“Exploring Machine Learning: Theory, Practice, and Innovations” is a thoughtfully curated resource that bridges the gap between foundational concepts and advanced methodologies in machine learning. With its systematic structure and practical orientation, the book caters to both beginners and experienced professionals in the field. The content is meticulously organised to align with the learner’s journey in understanding machine learning. The first chapter lays the groundwork by distinguishing human learning from machine learning, elucidating key concepts, and highlighting the potential and limitations of machine learning applications. A dedicated section on data preparation ensures readers grasp the significance of data preprocessing, quality enhancement, and exploration, setting the stage for successful modeling. The book’s core chapters address model selection, training, evaluation, and optimisation while introducing pivotal feature engineering techniques. Readers are guided through Bayes’ Theorem and its role in concept learning, followed by an exploration of supervised and unsupervised learning methods. Advanced algorithms, including decision trees, neural networks, and clustering techniques, are explained with clarity and context. Deep learning and neural networks are given special attention, with a focus on architecture, activation functions, and learning processes. The inclusion of contemporary topics such as ensemble learning and regularisation highlights the text’s relevance in modern machine learning landscapes. Practical insights are enriched by case studies across diverse applications, showcasing how theory translates into innovation. “Exploring Machine Learning” serves as a comprehensive, accessible, and indispensable guide for navigating the dynamic world of machine learning.
Introduction To Machine Learning In The Cloud With Python
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Author : Pramod Gupta
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Introduction To Machine Learning In The Cloud With Python written by Pramod Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Technology & Engineering categories.
This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.
Neurorobotics Explores Machine Learning
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Author : Fei Chen
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-20
Neurorobotics Explores Machine Learning written by Fei Chen 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 2023-01-20 with Science categories.
Reinforcement Learning
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Author : Richard S. Sutton
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Reinforcement Learning written by Richard S. Sutton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.
Efficient Learning Machines
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Author : Mariette Awad
language : en
Publisher: Apress
Release Date : 2015-04-27
Efficient Learning Machines written by Mariette Awad and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-27 with Computers categories.
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning.
Intelligent Computing And Big Data Analytics
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Author : Mukesh Patil
language : en
Publisher: Springer Nature
Release Date : 2024-12-30
Intelligent Computing And Big Data Analytics written by Mukesh Patil and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Computers categories.
This book constitutes the refereed proceedings of the First International Conference on Intelligent Computing and Big Data Analytics, ICICBDA 2024, held in Navi Mumbai, India, during June 15–16, 2024. The 48 full papers presented were carefully reviewed and selected from 275 submissions. The accepted submissions report original and novel results in various fields like Intelligent Security systems, Big Data Analytics, AI and ML applications, intelligent systems, Deep Learning, Blockchain, and many more.
Intelligent Computing Theories
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Author : De-Shuang Huang
language : en
Publisher: Springer
Release Date : 2013-07-20
Intelligent Computing Theories written by De-Shuang Huang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-20 with Computers categories.
This book constitutes the refereed conference proceedings of the 9th International Conference on Intelligent Computing, ICIC 2013, held in Nanning, China, in July 2013. The 74 revised full papers presented were carefully reviewed and selected from numerous submissions and are organized in topical sections on neural networks, nature inspired computing and optimization, cognitive science and computational neuroscience, knowledge discovery and data mining, evolutionary learning and genetic algorithms machine learning theory and methods, natural language processing and computational linguistics, fuzzy theory and models, soft computing, unsupervised and reinforced learning, intelligent computing in finance, intelligent computing in petri nets, intelligent data fusion and information security, virtual reality and computer interaction, intelligent computing in pattern recognition, intelligent computing in image processing, intelligent computing in robotics, complex systems theory and methods.
Closing The Loop Around Neural Systems
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Author : Steve M Potter
language : en
Publisher: Frontiers Media SA
Release Date : 2014-12-03
Closing The Loop Around Neural Systems written by Steve M Potter 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 2014-12-03 with Neurophysiology categories.
Closed-loop neurophysiology has been accelerated by recent software and hardware developments and by the emergence of novel tools to control neuronal activity with spatial and temporal precision, in which stimuli are delivered in real time based on recordings or behavior. Real-time stimulation feedback enables a wide range of innovative studies of information processing and plasticity in neuronal networks. This Research Topic e-Book comprises 16 Original Research Articles, seven Methods Articles, and seven Reviews, Mini- Reviews, and Perspectives, all peer-reviewed and published in Frontiers in Neural Circuits. The contributions deal with closed loop neurophysiology experiments at a variety of levels of neural circuit complexity. Some include modeling and theoretical analyses. New enabling technologies and techniques are described. Novel work is presented from experiments in vitro, in vivo, and in humans, along with their clinical and technological implications for improving the human condition.
Enhancing Music Education With Innovative Tools And Techniques
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Author : Lebedeva, Nadezhda Anatolievna
language : en
Publisher: IGI Global
Release Date : 2025-04-03
Enhancing Music Education With Innovative Tools And Techniques written by Lebedeva, Nadezhda Anatolievna and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-03 with Education categories.
Musical education is the process of acquiring the knowledge, skills, and abilities necessary for musical activity, as well as the body of knowledge and related skills and abilities obtained because of training. In today's rapidly evolving educational landscape, the integration of innovative tools and techniques transforms music education. By embracing technology, interactive platforms, and modern pedagogical strategies, educators enhance student engagement, improve skills, and foster a deeper appreciation for music. These innovations streamline traditional teaching methods while empowering students to explore music, ensuring music education remains relevant and inspiring. This shift revolutionizes how music is taught and experienced, preparing students for an ever-changing world of sound and performance. Enhancing Music Education With Innovative Tools and Techniques explores principles of educational training directly related to music education and it’s reflected in content, methods, and organizational forms. It examines the ways in which modern tools, technologies, and pedagogical approaches can be used to improve and transform music education, integrating digital technologies, software, apps, and other innovations to engage students in more interactive and creative ways. This book covers topics such as digital technology, music styles, and culture studies, and is a useful resource for musicians, educators, academicians, researchers, and scientists.
From Thinker To Doer Creativity Innovation Entrepreneurship Maker And Venture Capital
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Author : Yenchun Jim Wu
language : en
Publisher: Frontiers Media SA
Release Date : 2021-04-21
From Thinker To Doer Creativity Innovation Entrepreneurship Maker And Venture Capital written by Yenchun Jim Wu 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 2021-04-21 with Science categories.