ARTIFICIAL INTELLIGENCE ALGORITHMS FOR UNSUPERVISED LEARNING: CLUSTERING AND PATTERN RECOGNITION WITH NEURAL NETWORKS. Examples with MATLAB

Download ARTIFICIAL INTELLIGENCE ALGORITHMS FOR UNSUPERVISED LEARNING: CLUSTERING AND PATTERN RECOGNITION WITH NEURAL NETWORKS. Examples with MATLAB PDF Online Free

Author :
Publisher : SCIENTIFIC BOOKS
ISBN 13 :
Total Pages : 200 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!


Book Synopsis ARTIFICIAL INTELLIGENCE ALGORITHMS FOR UNSUPERVISED LEARNING: CLUSTERING AND PATTERN RECOGNITION WITH NEURAL NETWORKS. Examples with MATLAB by : CESAR PERZ LOPEZ

Download or read book ARTIFICIAL INTELLIGENCE ALGORITHMS FOR UNSUPERVISED LEARNING: CLUSTERING AND PATTERN RECOGNITION WITH NEURAL NETWORKS. Examples with MATLAB written by CESAR PERZ LOPEZ and published by SCIENTIFIC BOOKS. This book was released on with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence combines mathematical algorithms and techniques from Machine Learning, Deep Learning and Big Data to extract the knowledge contained in the data and present it in an understandable and automatic way. Neural networks and their applications are a fundamental tool to develop work in Artificial Intelligence. On the other hand, unsupervised learning is more closely aligned with Artificial Intelligence as it gives the idea that a machine can learn to identify complex processes and patterns without the need for a human to provide guidance and supervision throughout the learning process. Some examples of unsupervised learning algorithms include clustering and association rules. In the case of this type of learning, there is no pre-training data set; the problem is approached blindly and only with logical operations to guide it. Although at first glance it seems impossible, it is about the ability to solve complex problems using only input data and logical algorithms. This avoids the use of reference data. Unsupervised learning algorithms are used to discover hidden patterns in unlabeled data. Unlike supervised learning algorithms, where there is prior knowledge of the desired answers, these algorithms do not have a set of ordered data. They are responsible for determining the most important common characteristics of a group of information and then grouping them according to their similarities. Among the most interesting models are the neural networks. MATLAB implementrs the Deep Learning Toolbox specialized in the techniques of analytics based on neural networks. Throughout this book the techniques of analytics for clustering and classification based on neural networks are developed using MATLAB software

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models

Download Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models PDF Online Free

Author :
Publisher : Elsevier
ISBN 13 : 0128209348
Total Pages : 705 pages
Book Rating : 4.1/5 (282 download)

DOWNLOAD NOW!


Book Synopsis Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models by : Jorge Garza Ulloa

Download or read book Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models written by Jorge Garza Ulloa and published by Elsevier. This book was released on 2021-11-30 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. - Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems - Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems - Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others - Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients

MATLAB for Machine Learning

Download MATLAB for Machine Learning PDF Online Free

Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1788399390
Total Pages : 374 pages
Book Rating : 4.7/5 (883 download)

DOWNLOAD NOW!


Book Synopsis MATLAB for Machine Learning by : Giuseppe Ciaburro

Download or read book MATLAB for Machine Learning written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2017-08-28 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extract patterns and knowledge from your data in easy way using MATLAB About This Book Get your first steps into machine learning with the help of this easy-to-follow guide Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn Learn the introductory concepts of machine learning. Discover different ways to transform data using SAS XPORT, import and export tools, Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You'll start by getting your system ready with t he MATLAB environment for machine learning and you'll see how to easily interact with the Matlab workspace. We'll then move on to data cleansing, mining and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You'll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you'll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Digital Signal Processing with Matlab Examples, Volume 2

Download Digital Signal Processing with Matlab Examples, Volume 2 PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 9811025371
Total Pages : 944 pages
Book Rating : 4.8/5 (11 download)

DOWNLOAD NOW!


Book Synopsis Digital Signal Processing with Matlab Examples, Volume 2 by : Jose Maria Giron-Sierra

Download or read book Digital Signal Processing with Matlab Examples, Volume 2 written by Jose Maria Giron-Sierra and published by Springer. This book was released on 2016-12-02 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification.

Hospitality Management and Digital Transformation

Download Hospitality Management and Digital Transformation PDF Online Free

Author :
Publisher : Routledge
ISBN 13 : 100029675X
Total Pages : 303 pages
Book Rating : 4.0/5 (2 download)

DOWNLOAD NOW!


Book Synopsis Hospitality Management and Digital Transformation by : Richard Busulwa

Download or read book Hospitality Management and Digital Transformation written by Richard Busulwa and published by Routledge. This book was released on 2020-12-28 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hospitality managers are at a critical inflection point. Digital technology advancements are ramping up guest expectations and introducing nontraditional competitors that are beginning to disrupt the whole industry. The hospitality managers whose organizations are to thrive need to get their organizations into a position where they can effectively leverage digital technologies to simultaneously deliver breakthroughs in efficiency, agility, and guest experience. Hospitality Management and Digital Transformation is a much-needed guidebook to digital disruption and transformation for current and prospective hospitality and leisure managers. The book: • Explains digital technology advancements, how they cause disruption, and the implications of this disruption for hospitality and leisure organizations. • Explains the digital business and digital transformation imperative for hospitality and leisure organizations. • Discusses the different digital capabilities required to effectively compete as a digital business. • Discusses the new and/or enhanced roles hospitality and leisure managers need to play in effecting the different digital capabilities, as well as the competencies required to play these roles. • Discusses how hospitality and leisure managers can keep up with digital technology advancements. • Unpacks more than 36 key digital technology advancements, discussing what they are, how they work, and how they can be implemented across the hospitality and leisure industry. This book will be useful for advanced undergraduate and postgraduate students studying strategic management, IT, information systems, or digital business–related courses as part of degrees in hospitality and leisure management; as well as practitioners studying for professional qualifications.

Machine Learning

Download Machine Learning PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1315354411
Total Pages : 180 pages
Book Rating : 4.3/5 (153 download)

DOWNLOAD NOW!


Book Synopsis Machine Learning by : Mohssen Mohammed

Download or read book Machine Learning written by Mohssen Mohammed and published by CRC Press. This book was released on 2016-08-19 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and describing the areas of application for each algorithm, using simple practical examples to demonstrate each algorithm and showing how different issues related to these algorithms are applied.

MATLAB Deep Learning

Download MATLAB Deep Learning PDF Online Free

Author :
Publisher : Apress
ISBN 13 : 1484228456
Total Pages : 162 pages
Book Rating : 4.4/5 (842 download)

DOWNLOAD NOW!


Book Synopsis MATLAB Deep Learning by : Phil Kim

Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.

Navigating Digital Transformation in Management

Download Navigating Digital Transformation in Management PDF Online Free

Author :
Publisher : Taylor & Francis
ISBN 13 : 1000689506
Total Pages : 408 pages
Book Rating : 4.0/5 (6 download)

DOWNLOAD NOW!


Book Synopsis Navigating Digital Transformation in Management by : Richard Busulwa

Download or read book Navigating Digital Transformation in Management written by Richard Busulwa and published by Taylor & Francis. This book was released on 2022-10-31 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Navigating Digital Transformation in Management provides a thorough introduction to the implications of digital transformation for leaders and managers. The book clearly outlines what new or enhanced roles and activities digital transformation requires of them. The book takes a practical approach and shapes an actionable guide that students can take with them into their future careers as managers themselves. With core theoretical grounding, the book explains how the digital transformation imperative requires all organizations to continuously undertake digital business transformation to adapt to ongoing digital disruption and to effectively compete as digital businesses. The book discusses the critical roles managers need to play in establishing, facilitating, and accelerating the day-to-day activities required to build and continuously upgrade these capabilities. Drawing on cutting edge research, this textbook: Explains how digital technology advancements drive digital disruption and why digital business transformation and operating as a digital business are critical to organization survival Unpacks the different digital business capabilities required to effectively compete as a digital business Considers the new or digitally enhanced competencies required of leaders, managers, and their supporting professionals to effectively play their roles in digital transformation Discusses how leaders, managers, and their supporting professionals can keep up with digital technology advancements Unpacks key digital technology advancements, providing a plain language understanding of what they are, how they work, and their implications for organizations Enriched with pedagogical features to support understanding and reinforce learning, such as reflective questions, learning summaries, and case studies, and supported by a suite of instructor materials, this textbook is an ideal choice for teachers that want to enable their information systems, information technology, and digital business students to compete and thrive in the contemporary business environment.

Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection

Download Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1000454622
Total Pages : 395 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!


Book Synopsis Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection by : Almoataz Y. Abdelaziz

Download or read book Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection written by Almoataz Y. Abdelaziz and published by CRC Press. This book was released on 2021-10-22 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) can successfully help in solving real-world problems in power transmission and distribution systems because AI-based schemes are fast, adaptive, and robust and are applicable without any knowledge of the system parameters. This book considers the application of AI methods for the protection of different types and topologies of transmission and distribution lines. It explains the latest pattern-recognition-based methods as applicable to detection, classification, and location of a fault in the transmission and distribution lines, and to manage smart power systems including all the pertinent aspects. FEATURES Provides essential insight on uses of different AI techniques for pattern recognition, classification, prediction, and estimation, exclusive to power system protection issues Presents an introduction to enhanced electricity system analysis using decision-making tools Covers AI applications in different protective relaying functions Discusses issues and challenges in the protection of transmission and distribution systems Includes a dedicated chapter on case studies and applications This book is aimed at graduate students, researchers, and professionals in electrical power system protection, stability, and smart grids.

Artificial Intelligence in Biomedical and Modern Healthcare Informatics

Download Artificial Intelligence in Biomedical and Modern Healthcare Informatics PDF Online Free

Author :
Publisher : Elsevier
ISBN 13 : 0443218714
Total Pages : 656 pages
Book Rating : 4.4/5 (432 download)

DOWNLOAD NOW!


Book Synopsis Artificial Intelligence in Biomedical and Modern Healthcare Informatics by : M. A. Ansari

Download or read book Artificial Intelligence in Biomedical and Modern Healthcare Informatics written by M. A. Ansari and published by Elsevier. This book was released on 2024-10-03 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence in Biomedical and Modern Healthcare Informatics provides a deeper understanding of the current trends in AI and machine learning within healthcare diagnosis, its practical approach in healthcare, and gives insight into different wearable sensors and its device module to help doctors and their patients in enhanced healthcare system. The primary goal of this book is to detect difficulties and their solutions to medical practitioners for the early detection and prediction of any disease. The 56 chapters in the volume provide beginners and experts in the medical science field with general pictures and detailed descriptions of imaging and signal processing principles and clinical applications. With forefront applications and up-to-date analytical methods, this book captures the interests of colleagues in the medical imaging research field and is a valuable resource for healthcare professionals who wish to understand the principles and applications of signal and image processing and its related technologies in healthcare. - Discusses fundamental and advanced approaches as well as optimization techniques used in AI for healthcare systems - Includes chapters on various established imaging methods as well as emerging methods for skin cancer, brain tumor, epileptic seizures, and kidney diseases - Adopts a bottom-up approach and proposes recent trends in simple manner with the help of real-world examples - Synthesizes the existing international evidence and expert opinions on implementing decommissioning in healthcare - Promotes research in the field of health and hospital management in order to improve the efficiency of healthcare delivery systems

Applications of Hybrid Metaheuristic Algorithms for Image Processing

Download Applications of Hybrid Metaheuristic Algorithms for Image Processing PDF Online Free

Author :
Publisher : Springer Nature
ISBN 13 : 3030409775
Total Pages : 488 pages
Book Rating : 4.0/5 (34 download)

DOWNLOAD NOW!


Book Synopsis Applications of Hybrid Metaheuristic Algorithms for Image Processing by : Diego Oliva

Download or read book Applications of Hybrid Metaheuristic Algorithms for Image Processing written by Diego Oliva and published by Springer Nature. This book was released on 2020-03-27 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of the most recent hybrid methods for image processing. The algorithms included consider evolutionary, swarm, machine learning and deep learning. The respective chapters explore different areas of image processing, from image segmentation to the recognition of objects using complex approaches and medical applications. The book also discusses the theory of the methodologies used to provide an overview of the applications of these tools in image processing. The book is primarily intended for undergraduate and postgraduate students of science, engineering and computational mathematics, and can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence. Further, it is a valuable resource for researchers from the evolutionary computation, artificial intelligence and image processing communities.

Clustering Algorithms

Download Clustering Algorithms PDF Online Free

Author :
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 374 pages
Book Rating : 4.3/5 (91 download)

DOWNLOAD NOW!


Book Synopsis Clustering Algorithms by : John A. Hartigan

Download or read book Clustering Algorithms written by John A. Hartigan and published by John Wiley & Sons. This book was released on 1975 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shows how Galileo, Newton, and Einstein tried to explain gravity. Discusses the concept of microgravity and NASA's research on gravity and microgravity.

Applications of Artificial Intelligence in Medical Imaging

Download Applications of Artificial Intelligence in Medical Imaging PDF Online Free

Author :
Publisher : Academic Press
ISBN 13 : 0443184518
Total Pages : 381 pages
Book Rating : 4.4/5 (431 download)

DOWNLOAD NOW!


Book Synopsis Applications of Artificial Intelligence in Medical Imaging by : Abdulhamit Subasi

Download or read book Applications of Artificial Intelligence in Medical Imaging written by Abdulhamit Subasi and published by Academic Press. This book was released on 2022-11-10 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis. Discusses new deep learning algorithms for image analysis and how they are used for medical images Provides several examples for each imaging technique, along with their application areas so that readers can rely on them as a clinical decision support system Describes how new AI tools may contribute significantly to the successful enhancement of a single patient's clinical knowledge to improve treatment outcomes

Computational Intelligence in Time Series Forecasting

Download Computational Intelligence in Time Series Forecasting PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1846281849
Total Pages : 382 pages
Book Rating : 4.8/5 (462 download)

DOWNLOAD NOW!


Book Synopsis Computational Intelligence in Time Series Forecasting by : Ajoy K. Palit

Download or read book Computational Intelligence in Time Series Forecasting written by Ajoy K. Palit and published by Springer Science & Business Media. This book was released on 2006-01-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foresight in an engineering business can make the difference between success and failure, and can be vital to the effective control of industrial systems. The authors of this book harness the power of intelligent technologies individually and in combination.

Dissimilarity Representation For Pattern Recognition, The: Foundations And Applications

Download Dissimilarity Representation For Pattern Recognition, The: Foundations And Applications PDF Online Free

Author :
Publisher : World Scientific
ISBN 13 : 9814479144
Total Pages : 634 pages
Book Rating : 4.8/5 (144 download)

DOWNLOAD NOW!


Book Synopsis Dissimilarity Representation For Pattern Recognition, The: Foundations And Applications by : Robert P W Duin

Download or read book Dissimilarity Representation For Pattern Recognition, The: Foundations And Applications written by Robert P W Duin and published by World Scientific. This book was released on 2005-11-22 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a fundamentally new approach to pattern recognition in which objects are characterized by relations to other objects instead of by using features or models. This 'dissimilarity representation' bridges the gap between the traditionally opposing approaches of statistical and structural pattern recognition.Physical phenomena, objects and events in the world are related in various and often complex ways. Such relations are usually modeled in the form of graphs or diagrams. While this is useful for communication between experts, such representation is difficult to combine and integrate by machine learning procedures. However, if the relations are captured by sets of dissimilarities, general data analysis procedures may be applied for analysis.With their detailed description of an unprecedented approach absent from traditional textbooks, the authors have crafted an essential book for every researcher and systems designer studying or developing pattern recognition systems.

Machine Learning-Based Modelling in Atomic Layer Deposition Processes

Download Machine Learning-Based Modelling in Atomic Layer Deposition Processes PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1003803334
Total Pages : 353 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!


Book Synopsis Machine Learning-Based Modelling in Atomic Layer Deposition Processes by : Oluwatobi Adeleke

Download or read book Machine Learning-Based Modelling in Atomic Layer Deposition Processes written by Oluwatobi Adeleke and published by CRC Press. This book was released on 2023-12-15 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications. . .

Pattern Recognition and Machine Learning

Download Pattern Recognition and Machine Learning PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 9781493938438
Total Pages : 0 pages
Book Rating : 4.9/5 (384 download)

DOWNLOAD NOW!


Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop

Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.