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Artificial Intelligence And Machine Learning
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Book Synopsis Machine Learning and Artificial Intelligence by : Ameet V Joshi
Download or read book Machine Learning and Artificial Intelligence written by Ameet V Joshi and published by Springer Nature. This book was released on 2019-09-24 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Artificial Intelligence and Machine Learning Fundamentals by : Zsolt Nagy
Download or read book Artificial Intelligence and Machine Learning Fundamentals written by Zsolt Nagy and published by Packt Publishing Ltd. This book was released on 2018-12-12 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create AI applications in Python and lay the foundations for your career in data science Key FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail with interesting examplesMaster core AI concepts with engaging activitiesBook Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learnUnderstand the importance, principles, and fields of AIImplement basic artificial intelligence concepts with PythonApply regression and classification concepts to real-world problemsPerform predictive analysis using decision trees and random forestsCarry out clustering using the k-means and mean shift algorithmsUnderstand the fundamentals of deep learning via practical examplesWho this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
Author :Amit Ray Publisher :Compassionate AI Lab (An Imprint of Inner Light Publishers) ISBN 13 :9382123466 Total Pages :161 pages Book Rating :4.3/5 (821 download)
Book Synopsis Compassionate Artificial Intelligence by : Amit Ray
Download or read book Compassionate Artificial Intelligence written by Amit Ray and published by Compassionate AI Lab (An Imprint of Inner Light Publishers). This book was released on 2018-10-03 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book Dr. Amit Ray describes the principles, algorithms and frameworks for incorporating compassion, kindness and empathy in machine. This is a milestone book on Artificial Intelligence. Compassionate AI address the issues for creating solutions for some of the challenges the humanity is facing today, like the need for compassionate care-giving, helping physically and mentally challenged people, reducing human pain and diseases, stopping nuclear warfare, preventing mass destruction weapons, tackling terrorism and stopping the exploitation of innocent citizens by monster governments through digital surveillance. The book also talks about compassionate AI for precision medicine, new drug discovery, education, and legal system. Dr. Ray explained the DeepCompassion algorithms, five design principles and eleven key behavioral principle of compassionate AI systems. The book also explained several compassionate AI projects. Compassionate AI is the best practical guide for AI students, researchers, entrepreneurs, business leaders looking to get true value from the adoption of compassion in machine learning technology.
Book Synopsis Artificial Intelligence and Machine Learning for Business by : Steven Finlay
Download or read book Artificial Intelligence and Machine Learning for Business written by Steven Finlay and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence and Machine Learning for COVID-19 by : Fadi Al-Turjman
Download or read book Artificial Intelligence and Machine Learning for COVID-19 written by Fadi Al-Turjman and published by Springer Nature. This book was released on 2021-02-19 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is dedicated to addressing the major challenges in fighting COVID-19 using artificial intelligence (AI) and machine learning (ML) – from cost and complexity to availability and accuracy. The aim of this book is to focus on both the design and implementation of AI-based approaches in proposed COVID-19 solutions that are enabled and supported by sensor networks, cloud computing, and 5G and beyond. This book presents research that contributes to the application of ML techniques to the problem of computer communication-assisted diagnosis of COVID-19 and similar diseases. The authors present the latest theoretical developments, real-world applications, and future perspectives on this topic. This book brings together a broad multidisciplinary community, aiming to integrate ideas, theories, models, and techniques from across different disciplines on intelligent solutions/systems, and to inform how cognitive systems in Next Generation Networks (NGN) should be designed, developed, and evaluated while exchanging and processing critical health information. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via wireless/wired enabling technologies.
Book Synopsis Artificial Intelligence and Machine Learning in Public Healthcare by : KC Santosh
Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh and published by Springer Nature. This book was released on 2022-01-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.
Book Synopsis Machine Learning by : Phil Bernstein
Download or read book Machine Learning written by Phil Bernstein and published by Routledge. This book was released on 2022-04-30 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: ‘The advent of machine learning-based AI systems demands that our industry does not just share toys, but builds a new sandbox in which to play with them.’ - Phil Bernstein The profession is changing. A new era is rapidly approaching when computers will not merely be instruments for data creation, manipulation and management, but, empowered by artificial intelligence, they will become agents of design themselves. Architects need a strategy for facing the opportunities and threats of these emergent capabilities or risk being left behind. Architecture’s best-known technologist, Phil Bernstein, provides that strategy. Divided into three key sections – Process, Relationships and Results – Machine Learning lays out an approach for anticipating, understanding and managing a world in which computers often augment, but may well also supplant, knowledge workers like architects. Armed with this insight, practices can take full advantage of the new technologies to future-proof their business. Features chapters on: Professionalism Tools and technologies Laws, policy and risk Delivery, means and methods Creating, consuming and curating data Value propositions and business models.
Book Synopsis Artificial Intelligence, Machine Learning, and Deep Learning by : Oswald Campesato
Download or read book Artificial Intelligence, Machine Learning, and Deep Learning written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2020-01-23 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion. In addition, this book contains appendices for Keras, TensorFlow 2, and Pandas. Features: Covers an introduction to programming concepts related to AI, machine learning, and deep learning Includes material on Keras, TensorFlow2 and Pandas
Book Synopsis BASICS OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING by : Dr Dheeraj Mehrotra
Download or read book BASICS OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING written by Dr Dheeraj Mehrotra and published by Notion Press. This book was released on 2019-06-03 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of Artificial Intelligence (AI) & Machine Learning (ML) has been in practice for over years with the advent of technological progress. Over time, it has blended our lives through nearly every narration of learning, teaching, enjoyment, normal routine operations and what not. The aspect delivers a common understanding of the topics with reference to it making an impact on our lives, with a better framework of technology affecting our lives in particular. Let us look up to science for a change to be brought about in us. Let us create awareness of making technology available to people, in a broader sense. As that happens, people who are responsible need to be told about the use and misuse of the same. As we lead our lives, we come across the fact that AI, Robotics and Learning Machines seem to be the household topic of discussion. Earlier, AI was perceived to be reserved for only ‘Geniuses’ or ‘Researchers’ or the ‘computer’ community, but it very aptly integrates and impacts each and every aspect of our lives. Knowingly or unknowingly, it has become intellectually influential in shaping our thoughts, actions and the day-to-day chores.
Book Synopsis Artificial Intelligence and Machine Learning for Digital Pathology by : Andreas Holzinger
Download or read book Artificial Intelligence and Machine Learning for Digital Pathology written by Andreas Holzinger and published by Springer Nature. This book was released on 2020-06-24 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.
Book Synopsis AI and Machine Learning for Coders by : Laurence Moroney
Download or read book AI and Machine Learning for Coders written by Laurence Moroney and published by O'Reilly Media. This book was released on 2020-10-01 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving
Book Synopsis Machine Learning and Artificial Intelligence in Marketing and Sales by : Niladri Syam
Download or read book Machine Learning and Artificial Intelligence in Marketing and Sales written by Niladri Syam and published by Emerald Group Publishing. This book was released on 2021-03-10 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and Artificial Intelligence in Marketing and Sales explores the ideas, and the statistical and mathematical concepts, behind Artificial Intelligence (AI) and machine learning models, as applied to marketing and sales, without getting lost in the details of mathematical derivations and computer programming.
Book Synopsis Machine Learning for Kids by : Dale Lane
Download or read book Machine Learning for Kids written by Dale Lane and published by No Starch Press. This book was released on 2021-01-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+
Book Synopsis Artificial Intelligence and Machine Learning in Business Management by : Sandeep Kumar Panda
Download or read book Artificial Intelligence and Machine Learning in Business Management written by Sandeep Kumar Panda and published by CRC Press. This book was released on 2021-11-05 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Machine Learning in Business Management The focus of this book is to introduce artificial intelligence (AI) and machine learning (ML) technologies into the context of business management. The book gives insights into the implementation and impact of AI and ML to business leaders, managers, technology developers, and implementers. With the maturing use of AI or ML in the field of business intelligence, this book examines several projects with innovative uses of AI beyond data organization and access. It follows the Predictive Modeling Toolkit for providing new insight on how to use improved AI tools in the field of business. It explores cultural heritage values and risk assessments for mitigation and conservation and discusses on-shore and off-shore technological capabilities with spatial tools for addressing marketing and retail strategies, and insurance and healthcare systems. Taking a multidisciplinary approach for using AI, this book provides a single comprehensive reference resource for undergraduate, graduate, business professionals, and related disciplines.
Book Synopsis Artificial Intelligence and Deep Learning in Pathology by : Stanley Cohen
Download or read book Artificial Intelligence and Deep Learning in Pathology written by Stanley Cohen and published by Elsevier Health Sciences. This book was released on 2020-06-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.
Book Synopsis Artificial Intelligence and Machine Learning in Healthcare by : Ankur Saxena
Download or read book Artificial Intelligence and Machine Learning in Healthcare written by Ankur Saxena and published by Springer Nature. This book was released on 2021-05-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the application of artificial intelligence and machine learning in healthcare. It discusses integrating the principles of computer science, life science, and statistics incorporated into statistical models using existing data, discovering patterns in data to extract the information, and predicting the changes and diseases based on this data and models. The initial chapters of the book cover the practical applications of artificial intelligence for disease prognosis & management. Further, the role of artificial intelligence and machine learning is discussed with reference to specific diseases like diabetes mellitus, cancer, mycobacterium tuberculosis, and Covid-19. The chapters provide working examples on how different types of healthcare data can be used to develop models and predict diseases using machine learning and artificial intelligence. The book also touches upon precision medicine, personalized medicine, and transfer learning, with the real examples. Further, it also discusses the use of machine learning and artificial intelligence for visualization, prediction, detection, and diagnosis of Covid -19. This book is a valuable source of information for programmers, healthcare professionals, and researchers interested in understanding the applications of artificial intelligence and machine learning in healthcare.
Book Synopsis Artificial Intelligence by : Richard E. Neapolitan
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 466 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.
