Machine Learning Theoretical Foundations And Practical Applications
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Machine Learning Theoretical Foundations And Practical Applications
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Author : Manjusha Pandey
language : en
Publisher: Springer Nature
Release Date : 2021-04-19
Machine Learning Theoretical Foundations And Practical Applications written by Manjusha Pandey and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-19 with Technology & Engineering categories.
This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9–12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.
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.
Advances In Computer Vision From Deep Learning Models To Practical Applications
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Author : Hancheng Zhu
language : en
Publisher: Frontiers Media SA
Release Date : 2025-05-26
Advances In Computer Vision From Deep Learning Models To Practical Applications written by Hancheng Zhu 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 2025-05-26 with Science categories.
The field of computer vision has experienced remarkable progress in recent years, largely attributed to the unprecedented advancements in deep learning models and their practical applications across diverse domains. This research topic is dedicated to presenting and exploring the latest developments in computer vision, with a particular emphasis on the transition from theoretical deep learning models to their real-world applications. This research topic focuses on the practical application of deep learning models in computer vision, translating theoretical advancements into real-world solutions. It offers a platform to share success stories and case studies illustrating the effective deployment of such models in areas like medical imaging, remote sensing, and multimedia affective computing. Furthermore, with the importance of interpretability and transparency in deep learning models emphasized, these models become more complex and understanding their decision-making processes is crucial.
Machine Learning For Healthcare
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Author : Dr. R. C. Karpagalakshmi
language : en
Publisher: RK Publication
Release Date : 2024-05-23
Machine Learning For Healthcare written by Dr. R. C. Karpagalakshmi and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-23 with Computers categories.
Machine Learning for Healthcare the transformative impact of machine learning technologies on the healthcare industry. How machine learning algorithms are being used to enhance medical diagnostics, treatment plans, patient care, and operational efficiencies. It's key techniques such as predictive modeling, data analysis, and artificial intelligence applications, providing insights into real-world use cases and future trends. Suitable for healthcare professionals, data scientists, and researchers, this emphasizes the potential of machine learning in improving patient outcomes and revolutionizing healthcare delivery.
Foundations Of Probability Theory
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Author : Himadri Deshpande
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Foundations Of Probability Theory written by Himadri Deshpande and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Foundations of Probability Theory" offers a thorough exploration of probability theory's principles, methods, and applications. Designed for students, researchers, and practitioners, this comprehensive guide covers both foundational concepts and advanced topics. We begin with basic probability concepts, including sample spaces, events, probability distributions, and random variables, progressing to advanced topics like conditional probability, Bayes' theorem, and stochastic processes. This approach lays a solid foundation for further exploration. Our book balances theory and application, emphasizing practical applications and real-world examples. We cover topics such as statistical inference, estimation, hypothesis testing, Bayesian inference, Markov chains, Monte Carlo methods, and more. Each topic includes clear explanations, illustrative examples, and exercises to reinforce learning. Whether you're a student building a solid understanding of probability theory, a researcher exploring advanced topics, or a practitioner applying probabilistic methods to solve real-world problems, this book is an invaluable resource. We equip readers with the knowledge and tools necessary to tackle complex problems, make informed decisions, and explore probability theory's rich landscape with confidence.
Deep Learning Generalization
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Author : Liu Peng
language : en
Publisher: CRC Press
Release Date : 2025-09-12
Deep Learning Generalization written by Liu Peng and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-12 with Computers categories.
This book provides a comprehensive exploration of generalization in deep learning, focusing on both theoretical foundations and practical strategies. It delves deeply into how machine learning models, particularly deep neural networks, achieve robust performance on unseen data. Key topics include balancing model complexity, addressing overfitting and underfitting, and understanding modern phenomena such as the double descent curve and implicit regularization. The book offers a holistic perspective by addressing the four critical components of model training: data, model architecture, objective functions, and optimization processes. It combines mathematical rigor with hands-on guidance, introducing practical implementation techniques using PyTorch to bridge the gap between theory and real-world applications. For instance, the book highlights how regularized deep learning models not only achieve better predictive performance but also assume a more compact and efficient parameter space. Structured to accommodate a progressive learning curve, the content spans foundational concepts like statistical learning theory to advanced topics like Neural Tangent Kernels and overparameterization paradoxes. By synthesizing classical and modern views of generalization, the book equips readers to develop a nuanced understanding of key concepts while mastering practical applications. For academics, the book serves as a definitive resource to solidify theoretical knowledge and explore cutting-edge research directions. For industry professionals, it provides actionable insights to enhance model performance systematically. Whether you're a beginner seeking foundational understanding or a practitioner exploring advanced methodologies, this book offers an indispensable guide to achieving robust generalization in deep learning.
An Insight Into University Medical And Health Science Courses
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Author : Sunjoo Kang
language : en
Publisher: Frontiers Media SA
Release Date : 2022-12-26
An Insight Into University Medical And Health Science Courses written by Sunjoo Kang 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 2022-12-26 with Medical categories.
Interplay Of Artificial General Intelligence With Quantum Computing
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Author : C. Kishor Kumar Reddy
language : en
Publisher: Springer Nature
Release Date : 2025-08-12
Interplay Of Artificial General Intelligence With Quantum Computing written by C. Kishor Kumar Reddy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-12 with Computers categories.
This book investigates the dynamic relationship between artificial general intelligence (AGI) and quantum computing. AGI refers to a form of AI capable of performing any intellectual task that a human can, while quantum computing utilizes quantum mechanics principles to process information in fundamentally different ways compared to classical computing. This interplay explores how quantum computing might enhance AGI by accelerating complex computations and optimizing learning algorithms, potentially enabling AGI systems to solve problems beyond the reach of traditional computers. It also examines the challenges and opportunities presented by combining these technologies, including theoretical implications and practical applications in advancing AI capabilities. This book examines the groundbreaking intersection of artificial general intelligence (AGI) and quantum computing. The book explores how AGI, which aims to replicate human-like cognitive abilities, can be enhanced by quantum computing's unique processing capabilities. It delves into theoretical foundations, practical applications, and potential synergies, illustrating how quantum computing could tackle complex computational challenges inherent in AGI development. By integrating these advanced technologies, the book provides a comprehensive analysis of their combined impact, offering insights into future advancements and the transformative potential of merging AGI with quantum computing.
Algorithmic Learning Theory
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Author :
language : en
Publisher:
Release Date : 2004
Algorithmic Learning Theory written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computer algorithms categories.
Introduction To Time Series Analysis
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Author : Vikas Rathi
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Introduction To Time Series Analysis written by Vikas Rathi and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Introduction to Time Series Analysis" is a comprehensive guide exploring the world of time series data, blending theoretical insights with practical applications. Time series analysis is crucial across disciplines like economics, finance, engineering, and environmental science, helping us understand past patterns, forecast future trends, and make informed decisions. We cater to students, researchers, and practitioners seeking a deep understanding of time series analysis. Covering a range of topics from foundational concepts to advanced techniques, we ensure readers gain a holistic view of the subject. With clear explanations, illustrative examples, and real-world case studies, this book equips readers with the knowledge and skills needed to tackle complex time series data effectively. The book provides a solid theoretical foundation in time series analysis, covering topics such as time series decomposition, forecasting methods, and advanced modeling techniques. Emphasis is placed on practical applications, with real-world examples and case studies illustrating concepts and methodologies. The text is written in clear and accessible language, suitable for readers with varying expertise, and acknowledges the interdisciplinary nature of time series analysis, exploring its applications across different fields. Whether you're a student, researcher, or practitioner, "Introduction to Time Series Analysis" offers valuable insights and practical guidance to harness the power of time series data for informed decision-making.