Download or read book Unveiling Machine Learning Theory Algorithms and Practical Applications written by Dr.Padmaja Pulicherla and published by SK Research Group of Companies. This book was released on 2024-05-02 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.Padmaja Pulicherla, Professor, Department of Computer Science and Engineering, Hyderabad Institute of Technology and Management, Affiliated to JNTU, Hyderabad, Telangana, India. Dr.Kasarla Satish Reddy, Professor, Department of Electronics and Communication Engineering, Hyderabad Institute of Technology and Management, Affiliated to JNTU, Hyderabad, Telangana, India. D.Satyanarayana, Assistant Professor, Department of Computer Science and Engineering(DS), Santhiram Engineering College(Autonomous), Nandyal, Andhra Pradesh, India. Dr.R.Sudheer Babu, Associate Professor, Department of Electronics and Communication Engineering, G.Pulla Reddy Engineering College (Autonomous), Kurnool, Andhra Pradesh, India. Dr.Ravi Babu Devareddi, Assistant Professor, Department of Computer Science and Engineering, SRKR Engineering College, Bhimavaram, Andhra Pradesh, India.
Download or read book Machine Learning Refined written by Jeremy Watt and published by Cambridge University Press. This book was released on 2020-01-09 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: An intuitive approach to machine learning covering key concepts, real-world applications, and practical Python coding exercises.
Download or read book Information Theory Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.
Download or read book Chaos Unveiled written by Barrett Williams and published by Barrett Williams. This book was released on 2024-08-21 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: **Chaos Unveiled An Expedition into the Intricate World of Chaos Theory and Complex Systems** Unlock the mysteries of the universe's most captivating phenomenon with "Chaos Unveiled," an enlightening journey through chaos theory and complex systems. Crafted to engross and educate, this book serves as your definitive guide to understanding the unpredictable nature of the world around us. Dive into **Chapter 1** and explore the humble beginnings of chaos theory and its dramatic evolution into a pivotal scientific discipline. Discover key contributors and the milestones that have defined this groundbreaking field. Move into **Chapter 2**, where the intricate mathematics behind chaos comes to life. Understand nonlinear dynamics, sensitivity to initial conditions, and the enigmatic strange attractors that lead to seemingly random behaviors out of deterministic processes. In **Chapter 3**, delve into the mesmerizing world of fractals and self-similarity. From the beauty of fractal geometry to real-world applications, this chapter is a visual and intellectual feast. **Chapter 4** takes you into fluid dynamics, demystifying the complex phenomena of turbulence, vortices, and the iconic Lorenz attractor that revolutionized weather prediction and modeling. Explore the fascinating roles chaos plays in **biological systems** in **Chapter 5**, from population dynamics and cardiac rhythms to intricate ecosystems and food webs. Unravel the secrets of chaotic behavior in chemical reactions in **Chapter 6**, and discover how these principles govern both simple reactions and the complex chemistry of living organisms. Venture into **economic chaos** in **Chapter 7**, understanding stock market fluctuations, market bubbles, and the unpredictable nature of economic forecasting. The applications of chaos theory in **engineering** are unlocked in **Chapter 8**, revealing insights into control systems, structural analysis, and the ever-evolving field of robotics and machine learning. **Chapter 9** sheds light on chaos in social systems, from human behavior and social networks to the intricacies of urban planning. Experience medical breakthroughs in **Chapter 10**, where chaos theory enhances diagnostics, epidemiology, and our understanding of brain activity. Discover chaos in the vast expanse of **environmental science** and **astronomy** in **Chapters 11 and 12**, exploring climate change, earthquake prediction, orbital mechanics, and cosmic phenomena. **Chapter 13** provides groundbreaking insights into computational approaches, from numerical simulations to data analysis and pattern recognition. Reflect on the **philosophical implications** in **Chapter 14** as you weigh determinism against randomness and ponder the ethical considerations of predictability. Finally, look towards the **future of chaos theory** in **Chapter 15**, exploring emerging research areas, interdisciplinary collaborations, and the bright horizon of unanswered questions and challenges. "Chaos Unveiled" is not merely a book—it's an invitation to explore, question, and understand the beautifully intricate world of chaos theory. Get ready to have your mind expanded and your curiosity ignited!
Download or read book Practical Applications of Data Processing Algorithms and Modeling written by Whig, Pawan and published by IGI Global. This book was released on 2024-04-29 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.
Download or read book Deep Learning Theory and Applications written by Donatello Conte and published by Springer Nature. This book was released on 2023-07-30 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consitiutes the refereed proceedings of the 4th International Conference on Deep Learning Theory and Applications, DeLTA 2023, held in Rome, Italy from 13 to 14 July 2023. The 9 full papers and 22 short papers presented were thoroughly reviewed and selected from the 42 qualified submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding.
Download or read book Decoding CHATGPT and Artificial Intelligence written by Jagdish Krishanlal Arora and published by Jagdish Krishanlal Arora. This book was released on 2023-12-06 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step into the World of Revolutionary AI Ever wondered how artificial intelligence can mimic human conversation? Discover the intricacies of ChatGPT and AI in this comprehensive book, and prepare to have your mind expanded. Step inside the brains of one of the most advanced language models ever created, as you delve deep into its operation, boundaries, and the ethical considerations surrounding this groundbreaking technology. Curious about the magic behind AI's conversational power? Our detailed exploration will wash away the mystery and arm you with a profound understanding of AI's natural language generation capabilities. Through engaging and accessible programming code examples, you'll see firsthand how these models are built and how you can harness this technology to design your own AI creations. Feel the excitement as you journey through chapters that unravel the complexities of ChatGPT, revealing its training data and the sophisticated algorithms that guide its responses. With ethics at the forefront, you'll not only learn the technical side but also see the profound impact AI can have on society, for better or worse. Are you ready to embark on this thrilling adventure? Embrace the future today by arming yourself with knowledge from this insightful book. Whether you're a curious enthusiast or a seasoned programmer, the treasures within these pages promise to enlighten and inspire you to push the boundaries of what's possible with artificial intelligence. Your gateway to the wonders of ChatGPT and AI awaits. Are you ready to take the leap?
Download or read book Applications of Game Theory in Deep Learning written by Tanmoy Hazra and published by Springer Nature. This book was released on with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Network Science written by Carlos Andre Reis Pinheiro and published by John Wiley & Sons. This book was released on 2022-11-08 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network Science Network Science offers comprehensive insight on network analysis and network optimization algorithms, with simple step-by-step guides and examples throughout, and a thorough introduction and history of network science, explaining the key concepts and the type of data needed for network analysis, ensuring a smooth learning experience for readers. It also includes a detailed introduction to multiple network optimization algorithms, including linear assignment, network flow and routing problems. The text is comprised of five chapters, focusing on subgraphs, network analysis, network optimization, and includes a list of case studies, those of which include influence factors in telecommunications, fraud detection in taxpayers, identifying the viral effect in purchasing, finding optimal routes considering public transportation systems, among many others. This insightful book shows how to apply algorithms to solve complex problems in real-life scenarios and shows the math behind these algorithms, enabling readers to learn how to develop them and scrutinize the results. Written by a highly qualified author with significant experience in the field, Network Science also includes information on: Sub-networks, covering connected components, bi-connected components, community detection, k-core decomposition, reach network, projection, nodes similarity and pattern matching Network centrality measures, covering degree, influence, clustering coefficient, closeness, betweenness, eigenvector, PageRank, hub and authority Network optimization, covering clique, cycle, linear assignment, minimum-cost network flow, maximum network flow problem, minimum cut, minimum spanning tree, path, shortest path, transitive closure, traveling salesman problem, vehicle routing problem and topological sort With in-depth and authoritative coverage of the subject and many case studies to convey concepts clearly, Network Science is a helpful training resource for professional and industry workers in, telecommunications, insurance, retail, banking, healthcare, public sector, among others, plus as a supplementary reading for an introductory Network Science course for undergraduate students.
Download or read book Proceedings of the international conference on Machine Learning written by John Anderson and published by . This book was released on 19?? with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Introduction to Functional Nanomaterials written by M. Anusuya and published by CRC Press. This book was released on 2024-11-27 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive review of nanomaterials, including essential foundational examples of nanosensors, smart nanomaterials, nanopolymers, and nanotubes. Chapters cover their synthesis and characteristics, production methods, and applications, with specific sections exploring nanoelectronics and electro-optic nanotechnology, nanostructures, and nanodevices. This book is a valuable resource for interdisciplinary researchers who want to learn more about the synthesis of nanomaterials and how they are used in different types of energy storage devices, including supercapacitors, batteries, fuel cells solar cells in addition to electrical, chemical, and biomedical engineering. Key Features: Comprehensive overview of how nanomaterials can be utilised in a variety of interdisciplinary applications Explores the fundamental theories, alongside their electrochemical mechanisms and computation Discusses recent developments in electrode designing based on nanomaterials, separators, and the fabrication of advanced devices and their performances
Download or read book Advances in Digital Transformation Rise of Ultra Smart Fully Automated Cyberspace written by Eduard Babulak and published by BoD – Books on Demand. This book was released on 2024-07-17 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given the current research direction toward ubiquitous information sharing and digitalization, the huge amount of documents in the world’s largest libraries and archives are stored as digital data in big data centers, including those of Google, Apple, Microsoft, Samsung, Amazon, IBM, and others. The recent advancements in the fast Internet, smart computing, information technologies, and management information systems created a platform for ultra-smart cyberspace and cyber automation driven by digital transformation, artificial intelligence (AI), and ultra-smart humanoid robotics. Welcome to the world of the digital revolution and the new era of digitalization where the dream of paperless factories has become a reality today, and yet there are future challenges ahead of us to make sure that digitalization contributes to the betterment of humankind. This book is a valuable reference providing up-to-date information about current state-of-the-art and future research directions in digital transformation for cyber experts, business and industry practitioners, university faculty, and senior and graduate students worldwide.
Download or read book Bio inspired Computing Theories and Applications written by Maoguo Gong and published by Springer. This book was released on 2017-01-07 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set, CCIS 681 and CCIS 682, constitutes the proceedings of the 11th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2016, held in Xi'an, China, in October 2016.The 115 revised full papers presented were carefully reviewed and selected from 343 submissions. The papers of Part I are organized in topical sections on DNA Computing; Membrane Computing; Neural Computing; Machine Learning. The papers of Part II are organized in topical sections on Evolutionary Computing; Multi-objective Optimization; Pattern Recognition; Others.
Download or read book Introduction to Machine Learning with Applications in Information Security written by Mark Stamp and published by CRC Press. This book was released on 2022-09-27 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn’t prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.
Download or read book Process Neural Networks written by Xingui He and published by Springer Science & Business Media. This book was released on 2010-07-05 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.
Download or read book Statistical Process Monitoring Using Advanced Data Driven and Deep Learning Approaches written by Fouzi Harrou and published by Elsevier. This book was released on 2020-07-03 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Process Monitoring Using Advanced Data-Driven and Deep Learning Approaches tackles multivariate challenges in process monitoring by merging the advantages of univariate and traditional multivariate techniques to enhance their performance and widen their practical applicability. The book proceeds with merging the desirable properties of shallow learning approaches – such as a one-class support vector machine and k-nearest neighbours and unsupervised deep learning approaches – to develop more sophisticated and efficient monitoring techniques. Finally, the developed approaches are applied to monitor many processes, such as waste-water treatment plants, detection of obstacles in driving environments for autonomous robots and vehicles, robot swarm, chemical processes (continuous stirred tank reactor, plug flow rector, and distillation columns), ozone pollution, road traffic congestion, and solar photovoltaic systems. - Uses a data-driven based approach to fault detection and attribution - Provides an in-depth understanding of fault detection and attribution in complex and multivariate systems - Familiarises you with the most suitable data-driven based techniques including multivariate statistical techniques and deep learning-based methods - Includes case studies and comparison of different methods
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
