Machine Learning And Artificial Intelligence
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The Ultimate Modern Guide To Artificial Intelligence
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Author : Enamul Haque
language : en
Publisher: Enamul Haque
Release Date : 2020-07-21
The Ultimate Modern Guide To Artificial Intelligence written by Enamul Haque and has been published by Enamul Haque this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-21 with Computers categories.
The era of artificial intelligence has arrived. You, who only felt far from artificial intelligence, and the growing dream trees, are now inseparable from artificial intelligence. What does AI have to do with me? Isn't it a distant future that has nothing to do with me, not a scientist, a technician, or a computer programmer? Well, Artificial intelligence is not a story of someone who has nothing to do with it, but the fact is, it is now everyone's story. AI is already deeply infiltrating everyone's life. The question is no longer whether we use technology or not; it's about working together in a better way. Surrounding technologies like Siri, Alexa, or Cortana are seamlessly integrated into our interactions. We walk into the room, turn on the lights, play songs, change the room temperature, keep track of shopping lists, book a ride at the airport, or remind ourselves to take the proper medication on time. It is now necessary to look at artificial intelligence from a broader and larger perspective. You should not just hang on to complex deep learning algorithms and think only through science and technology but through the eyes of emotions and humanities. These days, elementary school students learn English and coding at school. Tomorrow's elementary school students will learn AI. Of course, not everyone needs to be an AI expert. But if you don't understand AI, you will be left out of the trend of changing times. AI comes before English and coding. This is because artificial intelligence is the language and tool of the future. This book opens your door to the most critical understanding needed of AI and other relevant disruptive technologies. Artificial intelligence will significantly change societal structures and the operations of companies. The next generation of employees needs to be trained as a workforce before entering the job market, and the existing workforce is regularly recharged and skilled. There is plenty on this for reskilling too. This is the most definitive compendium of AI, The Internet of Things, Machine Learning, Deep Learning, Data Science, Big Data, Cloud Computing, Neural networks, Robotics, the future of work and the future of intelligent industries.
The Simple Path To Learn Artificial Intelligence And Machine Learning
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Author : Charles Nehme
language : en
Publisher: Charles Nehme
Release Date :
The Simple Path To Learn Artificial Intelligence And Machine Learning written by Charles Nehme and has been published by Charles Nehme this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
In this book I summarise my learning experience in Machine learning and Artificial intelligence using Python programming language What is AI? Artificial intelligence is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. What is ML ? Machine learning is the study of computer algorithms that improve automatically through experience. It is seen as a part of artificial intelligence Enjoy this introductory ebook Keywords: AI, ML, Artificial intelligence, Machine learning, deep learning
Machine Learning
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Author : R.S. Michalski
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Machine Learning written by R.S. Michalski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Computers categories.
The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial intelligence, infor mation science, pattern recognition, psychology, education, epistemology, philosophy, and related disciplines. The recent observance of the silver anniversary of artificial intelligence has been heralded by a surge of interest in machine learning-both in building models of human learning and in understanding how machines might be endowed with the ability to learn. This renewed interest has spawned many new research projects and resulted in an increase in related scientific activities. In the summer of 1980, the First Machine Learning Workshop was held at Carnegie-Mellon University in Pittsburgh. In the same year, three consecutive issues of the Inter national Journal of Policy Analysis and Information Systems were specially devoted to machine learning (No. 2, 3 and 4, 1980). In the spring of 1981, a special issue of the SIGART Newsletter No. 76 reviewed current research projects in the field. . This book contains tutorial overviews and research papers representative of contemporary trends in the area of machine learning as viewed from an artificial intelligence perspective. As the first available text on this subject, it is intended to fulfill several needs.
Machine Learning And Artificial Intelligence With Industrial Applications
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Author : Diego Carou
language : en
Publisher: Springer
Release Date : 2023-03-12
Machine Learning And Artificial Intelligence With Industrial Applications written by Diego Carou and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-12 with Technology & Engineering categories.
This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
Artificial Intelligence And Machine Learning For Real World Applications
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Author : Latesh Malik
language : en
Publisher: CRC Press
Release Date : 2025-10-16
Artificial Intelligence And Machine Learning For Real World Applications written by Latesh Malik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-16 with Computers categories.
This book introduces foundational and advanced concepts in artificial intelligence (AI) and machine learning (ML), focusing on their real-world applications and societal implications. Covering topics from knowledge representation and model interpretability to deep learning and generative AI, Artificial Intelligence and Machine Learning for Real-World Applications: A Beginner's Guide with Case Studies includes practical Python implementations and case studies from healthcare, agriculture, and education. Beginning with core concepts such as AI fundamentals, knowledge representation, and statistical techniques, the text gradually advances to cover ML algorithms, deep learning architectures, and the basics of generative AI. Detailed discussions of data preprocessing, model training, evaluation metrics, and Python-based implementation make this book both practical and accessible. Offers real-world examples and case studies illustrating the societal impact and practical applications of AI and ML technologies Discusses data preprocessing techniques, model selection, and evaluation metrics with practical implementation in Python and in detail Explores AI problem-solving processes, knowledge representation, and model training strategies, catering to readers with varying levels of technical expertise Covers AI and ML principles spanning statistical techniques, ML algorithms, deep learning structures, and generative AI basics Focuses on societal applications in healthcare, agriculture, and education, addressing challenges faced by the elderly and special needs individuals This book is for professionals, researchers, and scholars interested in the application of AI and ML.
Explainable Artificial Intelligence An Introduction To Interpretable Machine Learning
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2021-12-16
Explainable Artificial Intelligence An Introduction To Interpretable Machine Learning written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-16 with Computers categories.
This book is written both for readers entering the field, and for practitioners with a background in AI and an interest in developing real-world applications. The book is a great resource for practitioners and researchers in both industry and academia, and the discussed case studies and associated material can serve as inspiration for a variety of projects and hands-on assignments in a classroom setting. I will certainly keep this book as a personal resource for the courses I teach, and strongly recommend it to my students. --Dr. Carlotta Domeniconi, Associate Professor, Computer Science Department, GMU This book offers a curriculum for introducing interpretability to machine learning at every stage. The authors provide compelling examples that a core teaching practice like leading interpretive discussions can be taught and learned by teachers and sustained effort. And what better way to strengthen the quality of AI and Machine learning outcomes. I hope that this book will become a primer for teachers, data Science educators, and ML developers, and together we practice the art of interpretive machine learning. --Anusha Dandapani, Chief Data and Analytics Officer, UNICC and Adjunct Faculty, NYU This is a wonderful book! I’m pleased that the next generation of scientists will finally be able to learn this important topic. This is the first book I’ve seen that has up-to-date and well-rounded coverage. Thank you to the authors! --Dr. Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, and Biostatistics & Bioinformatics Literature on Explainable AI has up until now been relatively scarce and featured mainly mainstream algorithms like SHAP and LIME. This book has closed this gap by providing an extremely broad review of various algorithms proposed in the scientific circles over the previous 5-10 years. This book is a great guide to anyone who is new to the field of XAI or is already familiar with the field and is willing to expand their knowledge. A comprehensive review of the state-of-the-art Explainable AI methods starting from visualization, interpretable methods, local and global explanations, time series methods, and finishing with deep learning provides an unparalleled source of information currently unavailable anywhere else. Additionally, notebooks with vivid examples are a great supplement that makes the book even more attractive for practitioners of any level. Overall, the authors provide readers with an enormous breadth of coverage without losing sight of practical aspects, which makes this book truly unique and a great addition to the library of any data scientist. Dr. Andrey Sharapov, Product Data Scientist, Explainable AI Expert and Speaker, Founder of Explainable AI-XAI Group
Artificial Intelligence And Machine Learning
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Author : Jeff Mc Frockman
language : en
Publisher:
Release Date : 2020-10-30
Artificial Intelligence And Machine Learning written by Jeff Mc Frockman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-30 with Business & Economics categories.
If you are interested in learning about artificial intelligence and machine learning or investing in these technological innovations, then ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING: AI Superpowers and Human+Machine A Visionary Revolution in Finance, Medicine and Business. Find Out Top Influent People of the Era With A Modern Approach, is the book that you have been waiting for. Although artificial intelligence and machine learning algorithms have been here with us for long, the ability to apply big data and make mathematical calculations even faster is a recent phenomenon. This book enlightens you on how the two technological developments have been able to speed up the process of economic growth and career advancement. To that end, this book provides an in-depth overview of artificial intelligence and machine learning, highlighting their historical development and application in various fields including finance, business, and medicine. It covers how artificial intelligence interacts with human intelligence, including the possible partnerships between humans and machines and how each influences the other. People can utilize so much from artificial intelligence and machine learning to improve their lives and enhance their productivity. An interesting concept covered in this book is the AI superpowers across the world, and how they impact the development of AI today and possibly in the future. These include Amit Singhal of Uber, Andrew Ng of Baidu, Elon Musk of SpaceX, and Tesla, among others. Artificial intelligence and machine learning are important tools that can promote development through enhanced production in various fields, including finance, medicine, business, and air. This is why you will learn how to invest in artificial intelligence, the possible benefits, and risks associated with the technology. Inside this book, you will find: Understanding of the definition, goals, advantages, and relationship of artificial intelligence and machine learning An overview of the relationship between artificial intelligence and human intelligence An outline of the key technology behind the Human-Machine Interface An overview of AI superpowers and AI key players An understanding of the 10 most influential people and their contribution to AI development And many more...
Artificial Intelligence And Machine Learning In Healthcare
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Author : Dharmendra Kumar Yadav
language : en
Publisher: Springer Nature
Release Date : 2023-10-29
Artificial Intelligence And Machine Learning In Healthcare written by Dharmendra Kumar Yadav and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-29 with Psychology categories.
This book is about the use of artificial intelligence (AI) and machine learning in healthcare. AI and related technologies are increasingly prevalent in business and society and are beginning to be applied to healthcare. These technologies have the potential to transform many aspects of patient care, as well as administrative processes within provider, payer, and pharmaceutical organizations. There are already a number of research studies suggesting that AI can perform as well as or better than humans at key healthcare tasks, such as diagnosing disease. Today, algorithms are already outperforming radiologists at spotting malignant tumors and guiding researchers in how to construct cohorts for costly clinical trials. However, for a variety of reasons, the authors believe that it will be many years before AI replaces humans for broad medical process domains. Through this book, the authors describe both the potential that AI offers to automate aspects of care and some of the barriers to rapid implementation of AI in healthcare.
Artificial Intelligence And Machine Learning For Edge Computing
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Author : Rajiv Pandey
language : en
Publisher: Academic Press
Release Date : 2022-04-26
Artificial Intelligence And Machine Learning For Edge Computing written by Rajiv Pandey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-26 with Science categories.
Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. - Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing - Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers - Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
Machine Learning And Artificial Intelligence
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Author : Ameet V Joshi
language : en
Publisher: Springer Nature
Release Date : 2019-09-24
Machine Learning And Artificial Intelligence written by Ameet V Joshi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-24 with Technology & Engineering categories.
This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible. Presents a full reference to artificial intelligence and machine learning techniques - in theory and application; Provides a guide to AI and ML with minimal use of mathematics to make the topics more intuitive and accessible; Connects all ML and AI techniques to applications and introduces implementations.