Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Handbook Of Machine Learning Volume 1 Foundation Of Artificial Intelligence full books in PDF, epub, and Kindle. Read online Handbook Of Machine Learning Volume 1 Foundation Of Artificial Intelligence ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Tshilidzi Marwala
Publisher :
ISBN 13 : 9789813271234
Total Pages : pages
Book Rating : 4.2/5 (712 download)
Download or read book Handbook of Machine Learning written by Tshilidzi Marwala and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Tshilidzi Marwala
Publisher : World Scientific
ISBN 13 : 9813271248
Total Pages : 329 pages
Book Rating : 4.8/5 (132 download)
Download or read book Handbook Of Machine Learning - Volume 1: Foundation Of Artificial Intelligence written by Tshilidzi Marwala and published by World Scientific. This book was released on 2018-10-22 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive book on the theories of artificial intelligence with an emphasis on their applications. It combines fuzzy logic and neural networks, as well as hidden Markov models and genetic algorithm, describes advancements and applications of these machine learning techniques and describes the problem of causality. This book should serves as a useful reference for practitioners in artificial intelligence.
Author : Tshilidzi Marwala
Publisher :
ISBN 13 : 9789813271227
Total Pages : pages
Book Rating : 4.2/5 (712 download)
Download or read book Handbook Of Machine Learning - Volume 1: Foundation Of Artif written by Tshilidzi Marwala and published by . This book was released on 2018-12-22 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Tshilidzi Marwala
Publisher : World Scientific
ISBN 13 : 981120568X
Total Pages : 321 pages
Book Rating : 4.8/5 (112 download)
Download or read book Handbook Of Machine Learning - Volume 2: Optimization And Decision Making written by Tshilidzi Marwala and published by World Scientific. This book was released on 2019-11-21 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.
Author : Monika Mangla
Publisher : CRC Press
ISBN 13 : 1000565726
Total Pages : 617 pages
Book Rating : 4.0/5 (5 download)
Download or read book Handbook of Research on Machine Learning written by Monika Mangla and published by CRC Press. This book was released on 2022-08-04 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation. The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.
Author : Plamen Parvanov Angelov
Publisher : World Scientific
ISBN 13 : 9811247331
Total Pages : 1057 pages
Book Rating : 4.8/5 (112 download)
Download or read book Handbook On Computer Learning And Intelligence (In 2 Volumes) written by Plamen Parvanov Angelov and published by World Scientific. This book was released on 2022-06-29 with total page 1057 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook on Computer Learning and Intelligence is a second edition which aims to be a one-stop-shop for the various aspects of the broad research area of computer learning and intelligence. This field of research evolved so much in the last five years that it necessitates this new edition of the earlier Handbook on Computational Intelligence.This two-volume handbook is divided into five parts. Volume 1 covers Explainable AI and Supervised Learning. Volume 2 covers three parts: Deep Learning, Intelligent Control, and Evolutionary Computation. The chapters detail the theory, methodology and applications of computer learning and intelligence, and are authored by some of the leading experts in the respective areas. The fifteen core chapters of the previous edition have been written and significantly refreshed by the same authors. Parts of the handbook have evolved to keep pace with the latest developments in computational intelligence in the areas that span across Machine Learning and Artificial Intelligence. The Handbook remains dedicated to applications and engineering-orientated aspects of these areas over abstract theories.Related Link(s)
Author : Ian Goodfellow
Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Author : Habib, Maki K.
Publisher : IGI Global
ISBN 13 : 1799886875
Total Pages : 589 pages
Book Rating : 4.7/5 (998 download)
Download or read book Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning written by Habib, Maki K. and published by IGI Global. This book was released on 2022-02-25 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: As technology spreads globally, researchers and scientists continue to develop and study the strategy behind creating artificial life. This research field is ever expanding, and it is essential to stay current in the contemporary trends in artificial life, artificial intelligence, and machine learning. This an important topic for researchers and scientists in the field as well as industry leaders who may adapt this technology. The Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning provides concepts, theories, systems, technologies, and procedures that exhibit properties, phenomena, or abilities of any living system or human. This major reference work includes the most up-to-date research on techniques and technologies supporting AI and machine learning. Covering topics such as behavior classification, quality control, and smart medical devices, it serves as an essential resource for graduate students, academicians, stakeholders, practitioners, and researchers and scientists studying artificial life, cognition, AI, biological inspiration, machine learning, and more.
Author : Richard E. Neapolitan
Publisher : CRC Press
ISBN 13 : 1351384384
Total Pages : 556 pages
Book Rating : 4.3/5 (513 download)
Download or read book Artificial Intelligence written by Richard E. Neapolitan and published by CRC Press. This book was released on 2018-03-12 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
Author : Dumpala Shanthi
Publisher : Bentham Science Publishers
ISBN 13 : 9815124528
Total Pages : 297 pages
Book Rating : 4.8/5 (151 download)
Download or read book Handbook of Artificial Intelligence written by Dumpala Shanthi and published by Bentham Science Publishers. This book was released on 2023-11-13 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) is an interdisciplinary science with multiple approaches to solve a problem. Advancements in machine learning (ML) and deep learning are creating a paradigm shift in virtually every tech industry sector. This handbook provides a quick introduction to concepts in AI and ML. The sequence of the book contents has been set in a way to make it easy for students and teachers to understand relevant concepts with a practical orientation. This book starts with an introduction to AI/ML and its applications. Subsequent chapters cover predictions using ML, and focused information about AI/ML algorithms for different industries (health care, agriculture, autonomous driving, image classification and segmentation, SEO, smart gadgets and security). Each industry use-case demonstrates a specific aspect of AI/ML techniques that can be used to create pipelines for technical solutions such as data processing, object detection, classification and more. Additional features of the book include a summary and references in every chapter, and several full-color images to visualize concepts for easy understanding. It is an ideal handbook for both students and instructors in undergraduate level courses in artificial intelligence, data science, engineering and computer science who are required to understand AI/ML in a practical context.
Author : Marc Peter Deisenroth
Publisher : Cambridge University Press
ISBN 13 : 1108569323
Total Pages : 392 pages
Book Rating : 4.1/5 (85 download)
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Author : Jon Adams
Publisher : Green Mountain Computing
ISBN 13 :
Total Pages : 117 pages
Book Rating : 4./5 ( download)
Download or read book AI Foundations of Machine Learning written by Jon Adams and published by Green Mountain Computing. This book was released on with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI Foundations of Machine Learning Embark on a clarifying expedition through the vibrant world of AI with "AI Foundations of Machine Learning." This comprehensive guide is meticulously crafted for those eager to unravel the complex mechanisms driving artificial intelligence and for pioneers looking to grasp the foundational stones of future technological advancements. From the fundamentals to the futuristic prospects, this book serves as both an educational journey and an initiation into the realm where data, computation, and potential converge. Contents: Understanding Supervised Learning: Begin your journey with an exploration of supervised learning, where machines learn from data with known outcomes, setting the stage for further complexities. The Mechanics of Unsupervised Learning: Delve into the artistry of AI as it uncovers hidden patterns without explicit instructions, highlighting the autonomy of machine learning. Diving into Neural Networks: Uncover the intricacies of neural networks, AI's approximation of the human brain, capable of recognizing speech, images, and nuances in vast datasets. The Decision Tree Paradigm: Discover the decision-making processes of AI through the decision tree paradigm, where data is systematically divided and conquered. Ensemble Methods Combining Strengths: Learn about the power of ensemble methods, which combine multiple models to enhance predictive accuracy and overcome individual weaknesses. Evaluating Model Performance: Understand the critical aspect of evaluating AI model performance, ensuring the integrity and applicability of machine learning applications. Machine Learning in the Real World: Witness the transformative impact of machine learning across various industries, from healthcare to finance, and how it reshapes our interaction with technology. The Future of Machine Learning: Gaze into the future, anticipating the breakthroughs and challenges of machine learning as it becomes an omnipresent force in our lives. This book is your gateway to understanding and participating in the future of AI, equipped with the knowledge to navigate and contribute to the advancements that lie ahead. Whether you are a student, professional, or enthusiast, "AI Foundations of Machine Learning" offers valuable insights into the ever-evolving field of machine learning, encouraging readers to not only understand but also to innovate in the unfolding story of AI.
Author : Dominic Lordy
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781720424604
Total Pages : 114 pages
Book Rating : 4.4/5 (246 download)
Download or read book Machine Learning with R written by Dominic Lordy and published by Createspace Independent Publishing Platform. This book was released on 2016-05-27 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***** BUY NOW (Will soon return to 25.59) ******Free eBook for customers who purchase the print book from Amazon****** Are you thinking of learning more about Machine Learning using R? If you are looking for a complete beginners guide to learn Machine Learning using R, in just a few hours, this book is for you. Machine Learning is the practice of transforming data into knowledge, and R is the most popular open-source programming language used for Machine Learning. In this book, we will learn how to use the principles of Machine Learning and the R programming language to answer day-to-day questions about your data. Finally, we'll learn how to make predictions with machine learning. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses. To get the most out of the concepts that would be covered, readers are advised to adopt hands on approach, which would lead to better mental representations. Several Visual Illustrations and Examples Instead of tough math formulas, this book contains several graphs and images which detail all important R and Machine Learning concepts and their applications. Target Users The book designed for a variety of target audiences. The most suitable users would include: Beginners who want to approach Machine Learning, but are too afraid of complex math to start Newbies in computer science techniques and machine learning Professionals in Machine Learning and social sciences Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way Students and academicians, especially those focusing on Machine Learning What's Inside This Book? Introduction Basic Functions Linear Regression Machine Learning Algorithms Data with R Generating data Graphical functions Programming with R in Practice Opening the Black Box K-nearest Neighbors Neural Networks Trees and Forests Standard Linear Model Logistic Regression Support Vector Machine using R Frequently Asked Questions Help! I got an error, what did I do wrong? Useful References Frequently Asked Questions Q: Is this book for me and do I need programming experience? A: f you want to smash Machine Learning from scratch, this book is for you. Little programming experience is required. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK. Q: Can I loan this book to friends? A: Yes. Under Amazon's Kindle Book Lending program, you can lend this book to friends and family for a duration of 14 days. Q: Does this book include everything I need to become a Machine Learning expert? A: Unfortunately, no. This book is designed for readers taking their first steps in Machine Learning and further learning will be required beyond this book to master all aspects of Machine Learning. Q: Can I have a refund if this book is not fitted for me? A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at [email protected]. If you need to see the quality of our job, AI Sciences Company offering you a free eBook in Machine Learning with Python written by the data scientist Alain Kaufmann at https: //aisciences.lpages.co/ai-sciences-data-science-with-r/
Author : Solanki, Arun
Publisher : IGI Global
ISBN 13 : 1522596453
Total Pages : 674 pages
Book Rating : 4.5/5 (225 download)
Download or read book Handbook of Research on Emerging Trends and Applications of Machine Learning written by Solanki, Arun and published by IGI Global. This book was released on 2019-12-13 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.
Author : Olivas, Emilio Soria
Publisher : IGI Global
ISBN 13 : 1605667676
Total Pages : 852 pages
Book Rating : 4.6/5 (56 download)
Download or read book Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques written by Olivas, Emilio Soria and published by IGI Global. This book was released on 2009-08-31 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Author : Sathiyamoorthi Velayutham
Publisher : IGI Global, Engineering Science Reference
ISBN 13 : 9781522599050
Total Pages : 0 pages
Book Rating : 4.5/5 (99 download)
Download or read book Handbook of Research on Applications and Implementations of Machine Learning Techniques written by Sathiyamoorthi Velayutham and published by IGI Global, Engineering Science Reference. This book was released on 2019-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book examines the practical applications and implementation of various machine learning techniques in various fields such as agriculture, medical, image processing, and networking"--
Author : Ryan Turner
Publisher :
ISBN 13 : 9781697522570
Total Pages : 172 pages
Book Rating : 4.5/5 (225 download)
Download or read book Machine Learning written by Ryan Turner and published by . This book was released on 2019-10-26 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★ Are you someone who is interested in how the next generation of machines can help you? Is Artificial Intelligence something to be feared, or do you imagine it that it will change our lives for the better? Do you want to know more?This book will provide the answers you need!Life is becoming ever more complex as we struggle to keep up with technology and use it to our best advantage. It is also more hectic and less certain, even in some of the mundane aspects of our lives, so that we are constantly trying to keep pace. New advancements in technology are paving the way to making life easier for billions and now things like Machine Learning and AI are changing the way we live.In this book, Machine Learning: The Ultimate Beginner's Guide to Learn Machine Learning, Artificial Intelligence & Neural Networks Step by Step, you will see how this new technology continuously improves itself, can identify trends and patterns with ease and handles a wide variety of data, with chapters that explore:: - Teaching the basic principles of Machine Learning- Why it is important and the many benefits that it provides- How Machine Learning differs from conventional programming- The fundamentals of algorithms- Challenges with Machine Learning and how you can easily overcome them- How it is going to change the future and make life easier- And much more...Machine Learning and AI are more than just science fiction. They are here now and undoubtedly will remain, improving and enhancing our lives in many ways, from the everyday to the vitally important. This book provides a platform that will give you a comprehensive understanding, that is second to none, of machine learning and its place in the world today.Get a copy nowand see how Machine Learning will change your life!
