Download or read book Systems that Learn written by Sanjay Jain and published by MIT Press. This book was released on 1999 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introduction to the concepts and techniques of formal learning theory is based on a number-theoretical approach to learning and uses the tools of recursive function theory to understand how learners come to an accurate view of reality.
Download or read book Systems That Learn written by Daniel N. Osherson and published by Bradford Books. This book was released on 1990 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems That Learn presents a mathematical framework for the study of learning in a variety of domains. It provides the basic concepts and techniques of learning theory as well as a comprehensive account of what is currently known about a variety of learning paradigms.Daniel N. Osherson and Scott Weinstein are at MIT, and Michael Stob at Calvin College.
Download or read book School Systems That Learn written by Paul B. Ash and published by Corwin Press. This book was released on 2012-12-04 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: When school systems learn, professional practice improves and student achievement increases Picture this: Teachers sharing insights and challenges. Principals leading with trust. Central office leaders inspiring and supporting principals. A synergistic learning system that results in all students succeeding. This practitioner's guide to creating a system-wide learning organization focuses on professional learning as the stimulus to improving student achievement. Experienced superintendents Paul Ash and John D'Auria provide a blueprint to: Improve schools through system-wide professional learning Increase student achievement by instilling a deep-rooted culture of curiosity Bolster faculty and staff morale with trust-building initiatives Align professional development with student-centered district standards
Download or read book Computer Systems that Learn written by Sholom M. Weiss and published by Morgan Kaufmann Publishers. This book was released on 1991 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is a practical guide to classification learning systems and their applications, which learn from sample data and make predictions for new cases. The authors examine prominent methods from each area, using an engineering approach and taking the practitioner's point of view.
Download or read book School Systems That Learn written by Paul B. Ash and published by Corwin Press. This book was released on 2012-12-04 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: When school systems learn, professional practice improves and student achievement increases Picture this: Teachers sharing insights and challenges. Principals leading with trust. Central office leaders inspiring and supporting principals. A synergistic learning system that results in all students succeeding. This practitioner′s guide to creating a system-wide learning organization focuses on professional learning as the stimulus to improving student achievement. Experienced superintendents Paul Ash and John D′Auria provide a blueprint to: Improve schools through system-wide professional learning Increase student achievement by instilling a deep-rooted culture of curiosity Bolster faculty and staff morale with trust-building initiatives Align professional development with student-centered district standards School Systems That Learn shows how professional development in a K-12 district can create synergy between educators and students that results in growth and achievement for all! "Paul Ash and John D′Auria draw on their deep understanding of school districts to help explain why so many American students are left behind. Their solution—to build the capacity of educators through collaboration and honest reflection—should make their book required reading for anyone who aspires to educational leadership." —Karin Chenoweth, Co-author of Getting It Done: Leading Academic Success in Unexpected Schools "This is a carefully developed and immensely practical guide for educators on how to build trust, develop collaborative capacity, and foster leadership at all levels—from the classroom teacher to the superintendent." —Amy C. Edmondson, Novartis Professor of Leadership and Management, Harvard Business School Author of Teaming: How Organizations Learn, Innovate and Compete in the Knowledge Economy
Download or read book Hands On Machine Learning with Scikit Learn Keras and TensorFlow written by Aurélien Géron and published by "O'Reilly Media, Inc.". This book was released on 2019-09-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
Download or read book The Learning Healthcare System written by Institute of Medicine and published by National Academies Press. This book was released on 2007-06-01 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: As our nation enters a new era of medical science that offers the real prospect of personalized health care, we will be confronted by an increasingly complex array of health care options and decisions. The Learning Healthcare System considers how health care is structured to develop and to apply evidence-from health profession training and infrastructure development to advances in research methodology, patient engagement, payment schemes, and measurement-and highlights opportunities for the creation of a sustainable learning health care system that gets the right care to people when they need it and then captures the results for improvement. This book will be of primary interest to hospital and insurance industry administrators, health care providers, those who train and educate health workers, researchers, and policymakers. The Learning Healthcare System is the first in a series that will focus on issues important to improving the development and application of evidence in health care decision making. The Roundtable on Evidence-Based Medicine serves as a neutral venue for cooperative work among key stakeholders on several dimensions: to help transform the availability and use of the best evidence for the collaborative health care choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and, ultimately, to ensure innovation, quality, safety, and value in health care.
Download or read book Learn Systems Thinking written by Wallace Wright and published by Charlie Creative Lab. This book was released on 2020-11-06 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: The challenges of the 21st century - from humanitarian to economic to environmental-demand new ways of thinking and more complex, flexible ways of acting. We no longer live in a disconnected world, due to the advances in technology and travel; a globalized world and economy require different approaches. "Systems thinking" is a highly developed and influential way of looking at the myriad and complicated interactions between humans, institutions, and natural processes.This book will help you understand the basics of systems thinking while providing you with the motivation to apply these tenants to your professional and personal life. From a thorough grounding in its basic principles to examples of how systems thinking works in real-time situations, the lessons and suggestions herein will guide you through the basic tenants, such as interconnectedness, synthesis, emergence, feedback loops, causality, and systems mapping. Move past the traditional forms of linear, mechanistic thinking to a more complex and dynamic way to solve problems, plan strategically, and make smarter decisions.Some of the specific material you will encounter in this book includes: An overall understanding of systems thinking and how each basic tenant leads to a greater understanding of this new approach to professional and personal success A detailed understanding of the archetypes that are identified within systems thinking, such as drifting goals and success to the successful, and how to utilize those archetypes in developing plans Chapters on how to specifically cultivate problem-solving skills, strategic planning, and forward-thinking decision making An understanding of mental modes and how we use them and how to change them to incorporate into our larger vision for the future A pragmatic guide to achieving success within a complex and dynamic world that requires new and original ways of thinking about how we interact with others and with systems themselves Whether you implement the practices of systems thinking within an organization or in your own interactions with the world, you will find it to be a dynamic and creative way to confront whatever challenges stand before you. The world in which we live isn't static; therefore, our responses to problem-solving and making smart decisions must also be active and engaged. Employing the new tools proposed by systems thinking will assist us cultivating this kind of adaptive and responsive skill set. Systems thinking encourages us to think in a three dimensional way and learning the terms and tools of this new approach to business, and the world can assist us in solving the complex problems that we face, as well as encourage us to plan well and make smarter decisions for our future.
Download or read book Adaptive Micro Learning written by Geng Sun (Researcher on educational technology) and published by World Scientific. This book was released on 2020 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Elements of Thinking in Systems written by Rutherford Albert and published by Dorottya Zita Varga. This book was released on 2019-08-16 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Would you like to have better solutions to your problems? Struggling to understand why things went wrong when you did everything right? Learn to Think in Systems can help you with these problems. Systems surround us and we might not even be aware of it. Your household is a system. The bakery on the corner is a system. Your class at school, your department at work, and your weekend soccer team made of wholehearted dads is a system too. You are a vital part of more complex systems like your country, the economy, or the world; learn about their changing nature, and find optimal solutions to problems related to them. The world is more connected than ever thanks to innovations like telephone, television, computers, and internet. The way we sense reality changed significantly. Using conventional thinking to understand the world as it functions today is not enough. We need to know the elements of systems thinking to see beyond simple cause-effect connections. This book will help you to find strategic solutions to every complex, modern problem. Learn To Think in Systems focuses on the nine fundamental system archetypes; our mental models related to them, and the step-by-step implication methods to fix them. Learn to use systems archetypes to solve your problems at work, in your business, in your relationship, and social connections. See through the motivations and understand the drives of contemporary politics, economics, and education. Widen your perspective, think critically, analyze deeply, clear your vision, be more logical and rational just by applying systems thinking. Think differently and get different results. -Learn the language of systems thinking. -Apply the best systems thinking ideas, models, and frameworks in your cognitive and decision-making process. -Learn to understand, design, and find solutions to the main system problems called 'archetypes.' Complexity, organizational pathways, and networks gain more and more importance in our interconnected world. Learn To Think in Systems gives you real-life examples to make the adoption process of this type of thinking smooth. Define your problems more accurately, find better, long-lasting solutions to your problems, learn to create strategic plans using systems diagrams, and understand your place and power over the world.
Download or read book Deep Learning for Vision Systems written by Mohamed Elgendy and published by Manning. This book was released on 2020-11-10 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside Image classification and object detection Advanced deep learning architectures Transfer learning and generative adversarial networks DeepDream and neural style transfer Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings
Download or read book Automated Machine Learning written by Frank Hutter and published by Springer. This book was released on 2019-05-17 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Download or read book Programming with POSIX Threads written by David R. Butenhof and published by Addison-Wesley Professional. This book was released on 1997 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software -- Operating Systems.
Download or read book Tools of Systems Thinkers written by Albert Rutherford and published by . This book was released on 2021-01-04 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Think with clarity, depth, and speed. Become an effective problem solver and decision maker. We often have blind spots for the actual reasons that cause problems in our lives. So we try to fix our issues based on assumptions, false analysis, and mistaken deductions. This can bring a lot of misunderstanding, anxiety, and frustration into our personal and work relationships.Tools of Systems Thinkers shares powerful strategies to organize your thoughts into transparent patterns and find the real roots of your problems and fix them once and for all.Notice details others miss. See through complexity. Resist jumping to conclusions prematurely. Evaluate information correctly and consistently to make better decisions. Stop sabotaging your self-interest. Overwrite your autopilot with logical and analytical tools. This unique book will give them to you. Learn to utilize mental models and system maps to your greatest advantage.Mental models provide transparency, order, deeper understanding, and context to your problem. System maps can become your leading cognitive tool to find a clear solution that lasts. Change your thinking, change your results.Albert Rutherford is an internationally bestselling author and a retired corporate executive. His books draw on various sources, from corporate system building, organizational behavior analysis, scientific research, and his life experience. He has been building and improving systems his whole adult life and brings his proven strategies to you. Regain focus. Discover relevant information. -Find out the 5 most powerful mental models and system maps.-Learn to create a visual representation of complex problems with dynamic systems.-Use system tools to fix your everyday problems.-Find real-life examples and exercises to deepen your knowledge at the end of each chapter. Make smart and clear decisions. Change your way of thinking. Master analytical, critical, and creative thinking. Become a systems thinker and discover how to approach your life from an entirely new perspective.
Download or read book Thinking in Systems written by Donella Meadows and published by Chelsea Green Publishing. This book was released on 2008-12-03 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classic book on systems thinking—with more than half a million copies sold worldwide! "This is a fabulous book... This book opened my mind and reshaped the way I think about investing."—Forbes "Thinking in Systems is required reading for anyone hoping to run a successful company, community, or country. Learning how to think in systems is now part of change-agent literacy. And this is the best book of its kind."—Hunter Lovins In the years following her role as the lead author of the international bestseller, Limits to Growth—the first book to show the consequences of unchecked growth on a finite planet—Donella Meadows remained a pioneer of environmental and social analysis until her untimely death in 2001. Thinking in Systems is a concise and crucial book offering insight for problem solving on scales ranging from the personal to the global. Edited by the Sustainability Institute’s Diana Wright, this essential primer brings systems thinking out of the realm of computers and equations and into the tangible world, showing readers how to develop the systems-thinking skills that thought leaders across the globe consider critical for 21st-century life. Some of the biggest problems facing the world—war, hunger, poverty, and environmental degradation—are essentially system failures. They cannot be solved by fixing one piece in isolation from the others, because even seemingly minor details have enormous power to undermine the best efforts of too-narrow thinking. While readers will learn the conceptual tools and methods of systems thinking, the heart of the book is grander than methodology. Donella Meadows was known as much for nurturing positive outcomes as she was for delving into the science behind global dilemmas. She reminds readers to pay attention to what is important, not just what is quantifiable, to stay humble, and to stay a learner. In a world growing ever more complicated, crowded, and interdependent, Thinking in Systems helps readers avoid confusion and helplessness, the first step toward finding proactive and effective solutions.
Download or read book Building Secure and Reliable Systems written by Heather Adkins and published by O'Reilly Media. This book was released on 2020-03-16 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can a system be considered truly reliable if it isn't fundamentally secure? Or can it be considered secure if it's unreliable? Security is crucial to the design and operation of scalable systems in production, as it plays an important part in product quality, performance, and availability. In this book, experts from Google share best practices to help your organization design scalable and reliable systems that are fundamentally secure. Two previous O’Reilly books from Google—Site Reliability Engineering and The Site Reliability Workbook—demonstrated how and why a commitment to the entire service lifecycle enables organizations to successfully build, deploy, monitor, and maintain software systems. In this latest guide, the authors offer insights into system design, implementation, and maintenance from practitioners who specialize in security and reliability. They also discuss how building and adopting their recommended best practices requires a culture that’s supportive of such change. You’ll learn about secure and reliable systems through: Design strategies Recommendations for coding, testing, and debugging practices Strategies to prepare for, respond to, and recover from incidents Cultural best practices that help teams across your organization collaborate effectively
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.
