Download or read book The Science of Artificial Intelligence Part 2 Mastering the Qualitative Learning Surface written by Michael Sinyangwe and published by . This book was released on 2019-03-20 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a framework for state-of-the-art machine learning techniques, which have been applied to the domain of sensual learning, thereby allowing AI systems to perceive the short-, medium-, and long-term configurations of their local environments. The focus is on machine image object recognition algorithms.
Download or read book The Sciences of the Artificial reissue of the third edition with a new introduction by John Laird written by Herbert A. Simon and published by MIT Press. This book was released on 2019-08-13 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Herbert Simon's classic work on artificial intelligence in the expanded and updated third edition from 1996, with a new introduction by John E. Laird. Herbert Simon's classic and influential The Sciences of the Artificial declares definitively that there can be a science not only of natural phenomena but also of what is artificial. Exploring the commonalities of artificial systems, including economic systems, the business firm, artificial intelligence, complex engineering projects, and social plans, Simon argues that designed systems are a valid field of study, and he proposes a science of design. For this third edition, originally published in 1996, Simon added new material that takes into account advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. Simon won the Nobel Prize for Economics in 1978 for his research into the decision-making process within economic organizations and the Turing Award (considered by some the computer science equivalent to the Nobel) with Allen Newell in 1975 for contributions to artificial intelligence, the psychology of human cognition, and list processing. The Sciences of the Artificial distills the essence of Simon's thought accessibly and coherently. This reissue of the third edition makes a pioneering work available to a new audience.
Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code
Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data
Download or read book Qualitative Research from Start to Finish First Edition written by Robert K. Yin and published by Guilford Press. This book was released on 2011-09-26 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This lively, practical text presents a fresh and comprehensive approach to doing qualitative research. The book offers a unique balance of theory and clear-cut choices for customizing every phase of a qualitative study. A scholarly mix of classic and contemporary studies from multiple disciplines provides compelling, field-based examples of the full range of qualitative approaches. Readers learn about adaptive ways of designing studies, collecting data, analyzing data, and reporting findings. Key aspects of the researcher's craft are addressed, such as fieldwork options, the five phases of data analysis (with and without using computer-based software), and how to incorporate the researcher's “declarative” and “reflective” selves into a final report. Ideal for graduate-level courses, the text includes:* Discussions of ethnography, grounded theory, phenomenology, feminist research, and other approaches.* Instructions for creating a study bank to get a new study started.* End-of-chapter exercises and a semester-long, field-based project.* Quick study boxes, research vignettes, sample studies, and a glossary.* Previews for sections within chapters, and chapter recaps.* Discussion of the place of qualitative research among other social science methods, including mixed methods research.
Download or read book Artificial Intelligence in Drug Discovery written by Nathan Brown and published by Royal Society of Chemistry. This book was released on 2020-11-04 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.
Download or read book The Coding Manual for Qualitative Researchers written by Johnny Saldana and published by SAGE. This book was released on 2009-02-19 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Coding Manual for Qualitative Researchers is unique in providing, in one volume, an in-depth guide to each of the multiple approaches available for coding qualitative data. In total, 29 different approaches to coding are covered, ranging in complexity from beginner to advanced level and covering the full range of types of qualitative data from interview transcripts to field notes. For each approach profiled, Johnny Saldaña discusses the method’s origins in the professional literature, a description of the method, recommendations for practical applications, and a clearly illustrated example.
Download or read book Resources in Education written by and published by . This book was released on 1989 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Qualitative Data Analysis written by Ian Dey and published by Routledge. This book was released on 2003-09-02 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.
Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Download or read book Machine Learning Algorithms written by Giuseppe Bonaccorso and published by Packt Publishing Ltd. This book was released on 2017-07-24 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide. Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation. Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide. Who This Book Is For This book is for IT professionals who want to enter the field of data science and are very new to Machine Learning. Familiarity with languages such as R and Python will be invaluable here. What You Will Learn Acquaint yourself with important elements of Machine Learning Understand the feature selection and feature engineering process Assess performance and error trade-offs for Linear Regression Build a data model and understand how it works by using different types of algorithm Learn to tune the parameters of Support Vector machines Implement clusters to a dataset Explore the concept of Natural Processing Language and Recommendation Systems Create a ML architecture from scratch. In Detail As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. Style and approach An easy-to-follow, step-by-step guide that will help you get to grips with real -world applications of Algorithms for Machine Learning.
Download or read book Artificial Intelligence written by George F. Luger and published by Pearson Higher Ed. This book was released on 2011-11-21 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one- or two-semester undergraduate course on AI. In this accessible, comprehensive text, George Luger captures the essence of artificial intelligence–solving the complex problems that arise wherever computer technology is applied. Ideal for an undergraduate course in AI, the Sixth Edition presents the fundamental concepts of the discipline first then goes into detail with the practical information necessary to implement the algorithms and strategies discussed. Readers learn how to use a number of different software tools and techniques to address the many challenges faced by today’s computer scientists.
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Qualitative Research written by Uwe Flick and published by SAGE. This book was released on 2009-02-19 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'The fourth edition of Uwe Flick's Introduction to Qualitative Research remains the most comprehensive and thorough text in qualitative research. It is student-and user-friendly, thoroughly up-to-date in terms of the latest developments in the field, imminently practical. it is the single most important introductory book on qualitative inquiry in the social sciences today' - Norman K. Denzin, University of Illinois The new edition of Uwe Flick's bestselling textbook has been fully revised, expanded and updated. An Introduction to Qualitative Research guides the student step-by-step through the research process of qualitative research. This classic text covers all of the main theoretical approaches to qualitative research, and provides unmatched coverage of the full range of different qualitative methods and approaches now available to researchers. A range of new features have been added to the new edition including: - New structure to better meet the needs of teaching qualitative research - A new chapter on Grounded Theory plus updated coverage on the full range of other qualitative methods - A summary section discussing the state-of-the-art in qualitative research - A glossary - Updated cases studies, exercises and guided questions This new edition will continue to ensure that An Introduction to Qualitative Research remains an essential introductory text for all students of qualitative research.
Download or read book Understanding the impact of artificial intelligence on skills development written by UNESCO International Centre for Technical and Vocational Education and Training and published by UNESCO Publishing. This book was released on 2021-04-02 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book How Learning Works written by Susan A. Ambrose and published by John Wiley & Sons. This book was released on 2010-04-16 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning
Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
