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Author: Albert Ziegler
Publisher: Frontiers Media SA
ISBN: 2889712621
Category : Science
Languages : en
Pages : 126
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Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262369303
Category : Computers
Languages : en
Pages : 858
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Book Description
A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
Author: Chester E. Finn, Jr.
Publisher: Princeton University Press
ISBN: 0691216916
Category : Education
Languages : en
Pages : 292
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Book Description
"More than three million high-school students take five million Advanced Placement exams each May, yet remarkably little is known about how this sixty-year-old, privately-run program, has become one of U.S. education's greatest successes. From its mid-century origin as a tiny option for privileged kids from posh schools, AP has also emerged as a booster rocket into college for hundreds of thousands of disadvantaged youngsters. It challenges smart kids, affects school ratings, affords rewarding classroom challenges to great teachers, tunes up entire schools, and draws vast support from philanthropists, education reformers and policymakers. AP stands as America's foremost source of college-level academics for high school pupils. Praised for its rigor and integrity, more than 22,000 schools now offer some-or many-of its thirty-eight subjects, from Latin to calculus, art to computer science. But challenges abound today, as AP faces stiffening competition (especially dual credit), curriculum wars, charges of elitism, misgivings by elite schools and universities, and the arduous work of infusing rigor into schools that lack it and academic success into young people unaccustomed to it. In today's polarized climate, can Advanced Placement maintain its lofty standards and overcome the hostility, politics and despair that have sunk so many other bold education ventures? Advanced Placement: The Unsung Success Story of American Education is a unique account-richly documented and thoroughly readable-of the AP program in all its strengths and travails, written by two of America's most respected education analysts"--
Author: Kevin Horsley
Publisher: Jaico Publishing House
ISBN: 9391019803
Category : Self-Help
Languages : en
Pages : 123
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Book Description
• Learn Faster • Remember More • Be More Productive YOU TOO CAN HAVE UNLIMITED MEMORY Do you need to remember large amounts of information? Do you find it hard to remember important things? Are you losing time by learning and relearning the same information over and over again? In the twenty-first century, learning faster and using your mind more effectively may be the only advantage that you will ever have over your competitors. This ultimate guide to memory improvement will show you how to train your memory, enhance your mental ability and keep your mind agile and alert. YOU’RE ABOUT TO DISCOVER: • The six most powerful memory systems that you can use to immediately improve your retention and recall • How to go from mastering only 7 bits of information in short-term memory to over 50 • How to easily remember what you have studied for tests and exams • How to improve your concentration and focus • How to remember names with ease in any social situation KEVIN HORSLEY is one of only a few people in the world to have received the title ‘International Grandmaster of Memory’. He is a World Memory Championship medalist and a World Record holder for ‘The Everest of Memory Tests’. Kevin is an international professional speaker and has spoken in many different countries. He assists organizations in improving their learning, motivation, creativity, and thinking.
Author: Kevin P. Murphy
Publisher: MIT Press
ISBN: 0262018020
Category : Computers
Languages : en
Pages : 1102
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Book Description
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Author: Taeho Jo
Publisher: Springer Nature
ISBN: 3030659003
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.
Author: National Geographic Learning
Publisher: Heinle ELT
ISBN: 9781337277198
Category : Education
Languages : en
Pages :
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Book Description
Author: Albert Ziegler
Publisher: Frontiers Media SA
ISBN: 2889712621
Category : Science
Languages : en
Pages : 126
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Book Description
Author: Pallavi Tyagi
Publisher: CRC Press
ISBN: 1003811590
Category : Education
Languages : en
Pages : 356
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Book Description
This book comprehensively covers the evolution of advanced learning pedagogy and innovative technologies like open educational resources and blended learning models. It specifically talks about the future of technology-enhanced learning and how advanced technology and government policies together are trying to impact learning outcomes globally. Nowadays in a flexible learning environment, technology plays a significant role in higher education systems. Both educators and students are playing prominent roles in its successful implementation. Advanced learning pedagogy by using technology has not only changed teaching procedures but has also evolved the relationship among multiple stakeholders. The content of the book is neatly segregated into four parts. Part I covers the concept and evolution of digital learning and education technology. This part examines the role of technology in higher education and proposes a toolkit for personalized learning and continuous assessment. Parts II and III creatively represent the innovative teaching techniques and learning models under advance learning pedagogy. Chapters under parts II and III are specially designed to present the more simplistic view of various technology-based advanced learning models and resources like flipped classes, gaming designs for e-learning, etc. Part III of the book also extensively covers various case studies/instructor’s stories of technology enabled learning experiences. Part IV focuses on the evaluation of advance learning pedagogy and tools. It also covers the future of information in learning (like formative analytics) and improved learning outcomes using technology and government initiatives in the form of various future oriented education policies like the Digital Action Education Plan (2021–2027). The wide-ranging content also covers the challenges of implementation of advanced learning pedagogy and offers recommendations to overcome such challenges. The book will grab the attention of the modern (IT-enabled) instructor’s fraternity, and students and researchers in the area of technology and education. The book can be further used by policymakers and educational-technology startups to formulate and design technology-based higher education teaching policies and procedures which are indeed helpful in measuring learning outcomes.
Author: J. Michael Spector
Publisher: SAGE Publications
ISBN: 1506311296
Category : Education
Languages : en
Pages : 1839
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Book Description
The SAGE Encyclopedia of Educational Technology examines information on leveraging the power of technology to support teaching and learning. While using innovative technology to educate individuals is certainly not a new topic, how it is approached, adapted, and used toward the services of achieving real gains in student performance is extremely pertinent. This two-volume encyclopedia explores such issues, focusing on core topics and issues that will retain relevance in the face of perpetually evolving devices, services, and specific techniques. As technology evolves and becomes even more low-cost, easy-to-use, and more accessible, the education sector will evolve alongside it. For instance, issues surrounding reasoning behind how one study has shown students retain information better in traditional print formats are a topic explored within the pages of this new encyclopedia. Features: A collection of 300-350 entries are organized in A-to-Z fashion in 2 volumes available in a choice of print or electronic formats. Entries, authored by key figures in the field, conclude with cross references and further readings. A detailed index, the Reader’s Guide themes, and cross references combine for search-and-browse in the electronic version. This reference encyclopedia is a reliable and precise source on educational technology and a must-have reference for all academic libraries.
Author:
Publisher:
ISBN:
Category : Artillery, Field and mountain
Languages : en
Pages : 300
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