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Machine Learning - Seyedeh Leili (electrical And Computer Engineering Dept Mirtaheri - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning - Seyedeh Leili (electrical And Computer Engineering Dept Mirtaheri - Bog - Taylor & Francis Ltd - Plusbog.dk

The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorithms. Unlike the existing literature, this work provides the core concepts with emphasis on fresh ideas and real application scenarios. It starts with the basic concepts of ML and extends the concepts to the different deep learning algorithms. The book provides an introduction and main elements of evaluation tools with Python and walks you through the recent applications of ML in self-driving cars, cognitive decision making, communication networks, security, and signal processing. The concept of generative networks is also presented and focuses on GANs as a tool to improve the performance of existing algorithms. In summary, this book provides a comprehensive technological path from fundamental theories to the categorization of existing algorithms, covers state-of-the-art, practical evaluation tools and methods to empower you to use synthetic data to improve the performance of applications.

DKK 579.00
3

Machine Learning in Signal Processing - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning in Signal Processing - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects - Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

DKK 468.00
3

Machine Learning in Multimedia - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning in Multimedia - - Bog - Taylor & Francis Ltd - Plusbog.dk

This book explores the interdisciplinary nature of machine learning in multimedia, highlighting its intersections with fields such as computer vision, natural language processing, and audio signal processing. Machine Learning in Multimedia: Unlocking the Power of Visual and Auditory Intelligence serves as a comprehensive guide to navigating this exciting terrain where artificial intelligence meets the rich tapestry of visual and auditory data. At its core, this book seeks to unravel the mysteries and unveil the potential of machine learning in the realm of multimedia. Whether it''s enhancing user experiences in virtual environments, revolutionizing medical diagnostics, or shaping the future of entertainment, the impact of machine learning in multimedia is profound and far-reaching. The journey begins with a thorough exploration of the foundational principles of machine learning, providing readers with a solid understanding of algorithms, models, and techniques tailored specifically for multimedia data. Through clear explanations and illustrative examples, readers will gain insights into how machine learning algorithms can be trained to extract meaningful patterns and insights from diverse forms of multimedia content. Moving beyond theory, this book delves into practical implementations and real-world applications of machine learning in multimedia. Through a series of case studies and examples, readers will witness firsthand how machine learning algorithms are transforming industries and reshaping the way we interact with multimedia content. Whether it''s improving image recognition accuracy in autonomous vehicles, enabling personalized recommendations in streaming platforms, or enhancing speech recognition systems for better accessibility, the possibilities are limitless. This book will be helpful to computer science, data science, and artificial intelligence researchers, students, and professionals looking to unlock the full potential of visual and auditory intelligence through the power of machine learning.

DKK 759.00
3

Quantum Machine Learning - - Bog - Taylor & Francis Ltd - Plusbog.dk

Quantum Machine Learning - - Bog - Taylor & Francis Ltd - Plusbog.dk

This book presents the research into and application of machine learning in quantum computation, known as quantum machine learning (QML). It presents a comparison of quantum machine learning, classical machine learning, and traditional programming, along with the usage of quantum computing, toward improving traditional machine learning algorithms through case studies. In summary, the book: - - Covers the core and fundamental aspects of statistics, quantum learning, and quantum machines. - - - Discusses the basics of machine learning, regression, supervised and unsupervised machine learning algorithms, and artificial neural networks. - - - Elaborates upon quantum machine learning models, quantum machine learning approaches and quantum classification, and boosting. - - - Introduces quantum evaluation models, deep quantum learning, ensembles, and QBoost. - - - Presents case studies to demonstrate the efficiency of quantum mechanics in industrial aspects. - This reference text is primarily written for scholars and researchers working in the fields of computer science and engineering, information technology, electrical engineering, and electronics and communication engineering.

DKK 901.00
1

Machine Elements - Frederic E. Nystrom - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Elements - Frederic E. Nystrom - Bog - Taylor & Francis Ltd - Plusbog.dk

Focusing on how a machine "feels" and behaves while operating, Machine Elements: Life and Design seeks to impart both intellectual and emotional comprehension regarding the "life" of a machine. It presents a detailed description of how machines elements function, seeking to form a sympathetic attitude toward the machine and to ensure its wellbeing through more careful and proper design. The book is divided into three sections for accessibility and ease of comprehension. The first section is devoted to microscopic deformations and displacements both in permanent connections and within the bodies of stressed parts. Topics include relative movements in interference fit connections and bolted joints, visual demonstrations and clarifications of the phenomenon of stress concentration, and increasing the load capacity of parts using prior elasto-plastic deformation and surface plastic deformation. The second part examines machine elements and units. Topics include load capacity calculations of interference fit connections under bending, new considerations about the role of the interference fit in key joints, a detailed examination of bolts loaded by eccentrically applied tension forces, resistance of cylindrical roller bearings to axial displacement under load, and a new approach to the choice of fits for rolling contact bearings. The third section addresses strength calculations and life prediction of machine parts. It includes information on the phenomena of static strength and fatigue; correlation between calculated and real strength and safety factors; and error migration.

DKK 662.00
3

Machine Vision for Industry 4.0 - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Vision for Industry 4.0 - - Bog - Taylor & Francis Ltd - Plusbog.dk

- This book discusses the use of machine vision and technologies in specific engineering case studies and focuses on how machine vision techniques are impacting every step of industrial processes and how smart sensors and cognitive big data analytics are supporting the automation processes in Industry 4.0 applications. - Industry 4.0, the Fourth Industrial Revolution, combines traditional manufacturing with automation and data exchange. Machine vision is used in the industry for reliable product inspections, quality control, and data capture solutions. It combines different technologies to provide important information from the acquisition and analysis of images for robot-based inspection and guidance. - Features - - Presents a comprehensive guide on how to use machine vision for Industry 4.0 applications, such as analysis of images for automated inspections, object detection, object tracking, and more - - - Includes case studies of Robotics Internet of Things with its current and future applications in healthcare, agriculture, and transportation - - - Highlights the inclusion of impaired people in the industry, for example, an intelligent assistant that helps deaf-mute individuals to transmit instructions and warnings in a manufacturing process - - - Examines the significant technological advancements in machine vision for Industrial Internet of Things and explores the commercial benefits using real-world applications from healthcare to transportation - - - Discusses a conceptual framework of machine vision for various industrial applications - The book addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and postgraduate students, researchers, and anyone interested in the trends, development, and opportunities for machine vision for Industry 4.0 applications.

DKK 486.00
3

Machine Tools - - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Tools - - Bog - Taylor & Francis Ltd - Plusbog.dk

This book introduces the applications of Industry 4.0 in machine tools through an overview of the latest available digital technologies. It focuses on digital twining, communication between industrial controls, motion, and input/output devices, along with sustainability in SMEs. Machine Tools: An Industry 4.0 Perspective focuses on the digital twining of machine tools, which improves the life of the machines and provides a method of operating a factory during times of complete lockdown resulting from various conditions. It presents an overview of the communication between industrial controls, motion, and input/output devices through standardized digital interfaces such as SERCOS and USB. The book goes on to discuss industrial cybersecurity systems applicable to discrete manufacturing, which includes cyberattacks and human errors, and address the security aspects related to software, hardware, and data. The book also explores the application of big data for different stages of production and illustrates the uses such as predictive maintenance, product quality, product life cycle management (PLM), and more. This book is an ideal reference for undergraduate, graduate, and postgraduate students of industrial, mechanical, and mechatronics engineering, along with professionals, and general readers.

DKK 505.00
3

Machine Learning for Neuroscience - Chuck Easttom - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning for Neuroscience - Chuck Easttom - Bog - Taylor & Francis Ltd - Plusbog.dk

This book addresses the growing need for machine learning and data mining in neuroscience. The book offers a basic overview of the neuroscience, machine learning and the required math and programming necessary to develop reliable working models. The material is presented in a easy to follow user-friendly manner and is replete with fully working machine learning code. Machine Learning for Neuroscience: A Systematic Approach, tackles the needs of neuroscience researchers and practitioners that have very little training relevant to machine learning. The first section of the book provides an overview of necessary topics in order to delve into machine learning, including basic linear algebra and Python programming. The second section provides an overview of neuroscience and is directed to the computer science oriented readers. The section covers neuroanatomy and physiology, cellular neuroscience, neurological disorders and computational neuroscience. The third section of the book then delves into how to apply machine learning and data mining to neuroscience and provides coverage of artificial neural networks (ANN), clustering, and anomaly detection. The book contains fully working code examples with downloadable working code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook. The primary audience is neuroscience researchers who need to delve into machine learning, programmers assigned neuroscience related machine learning projects and students studying methods in computational neuroscience.

DKK 929.00
3

Machine Learning and its Applications - Peter Wlodarczak - Bog - Taylor & Francis Ltd - Plusbog.dk

Machine Learning and its Applications - Peter Wlodarczak - Bog - Taylor & Francis Ltd - Plusbog.dk

In recent years, machine learning has gained a lot of interest. Due to the advances in processor technology and the availability of large amounts of data, machine learning techniques have provided astounding results in areas such as object recognition or natural language processing. New approaches, e.g. deep learning, have provided groundbreaking outcomes in fields such as multimedia mining or voice recognition. Machine learning is now used in virtually every domain and deep learning algorithms are present in many devices such as smartphones, cars, drones, healthcare equipment, or smart home devices. The Internet, cloud computing and the Internet of Things produce a tsunami of data and machine learning provides the methods to effectively analyze the data and discover actionable knowledge. This book describes the most common machine learning techniques such as Bayesian models, support vector machines, decision tree induction, regression analysis, and recurrent and convolutional neural networks. It first gives an introduction into the principles of machine learning. It then covers the basic methods including the mathematical foundations. The biggest part of the book provides common machine learning algorithms and their applications. Finally, the book gives an outlook into some of the future developments and possible new research areas of machine learning and artificial intelligence in general. This book is meant to be an introduction into machine learning. It does not require prior knowledge in this area. It covers some of the basic mathematical principle but intends to be understandable even without a background in mathematics. It can be read chapter wise and intends to be comprehensible, even when not starting in the beginning. Finally, it also intends to be a reference book. Key Features: Describes real world problems that can be solved using Machine Learning Provides methods for directly applying Machine Learning techniques to concrete real world problems Demonstrates how to apply Machine Learning techniques using different frameworks such as TensorFlow, MALLET, R

DKK 505.00
3