deep learning for cognitive computing systems

Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. The integration of deep learning improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data sets and generating meaningful insights.

Objev podobné jako Deep Learning for Cognitive Computing Systems

Humans do a great job of reading text, identifying key ideas, summarizing, making connections, and other tasks that require comprehension and context. Recent advances in deep learning make it possible for computer systems to achieve similar results. Deep Learning for Natural Language Processing teaches you to apply deep learning methods to natural language processing (NLP) to interpret and use text effectively. In this insightful book, (NLP) expert Stephan Raaijmakers distills his extensive knowledge of the latest state-of-the-art developments in this rapidly emerging field. Key features An overview of NLP and deep learning • Models for textual similarity • Deep memory-based NLP • Semantic role labeling • Sequential NLP Audience For those with intermediate Python skills and general knowledge of NLP. No hands-on experience with Keras or deep learning toolkits is required. About the technology Natural language processing is the science of teaching computers to interpret and process human language. Recently, NLP technology has leapfrogged to exciting new levels with the application of deep learning, a form of neural network-based machine learning Stephan Raaijmakers is a senior scientist at TNO and holds a PhD in machine learning and text analytics. He’s the technical coordinator of two large European Union-funded research security-related ... Unknown localization key: "more"

Objev podobné jako Deep Learning for Natural Language Processing - Stephan Raaijmakers

Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems.This book discusses crack-like object detection problem comprehensively. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. It provides a detailed review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

Objev podobné jako Deep Learning for Crack-Like Object Detection - Heng-Da Cheng, Kaige Zhang

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This step-by-step guide teaches you how to build practical deep learning applications for the cloud and mobile using a hands-on approach.

Objev podobné jako Practical Deep Learning for Cloud and Mobile - Anirudh Koul, Siddha Ganju, Meher Kasam

Whether they are new or experienced, teachers are expected to plan and deliver high-quality computing lessons to their pupils. Computing and Digital Learning for Primary Teachers provides an accessible introduction to teaching computing effectively and for deeper understanding in the primary classroom.Filled with practical resources to support lesson design, long-term planning, and assessment, readers will benefit from building their subject knowledge and learning to create engaging lessons for their pupils. Chapters explore:Supporting computational thinking and problem-solving to teach our pupils how to solve problems logically and systematically.Developing pupils’ digital literacy and use of IT, creating exciting opportunities for children’s digital self-expression through film, animation, and 3D design.Managing technology in our schools, such as setting up and maintaining a virtual learning environment (VLE).Cross-curriculum links with STEAM and engineering, allowing children to solve real-world problems by combining their digital literacy with their knowledge of maths, science, and technology.Cost-effective and accessible ways of introducing physical computing and robotics to children.Safe and responsible uses of artificial intelligence (AI) in our primary schools.This essential resource provides a highly practical guide to delivering effective computing lessons in the primary classroom and is a must read for anyone who wishes to become a more confident and knowledgeable ... Unknown localization key: "more"

Objev podobné jako Computing and Digital Learning for Primary Teachers - Owen Dobbing

This book explores intelligent systems in computing and informatics, focusing specifically on their role in advancing Sustainable Development Goal (SDG) No. 11 – Sustainable Cities and Communities.SDG 11 is part of the 17 Sustainable Development Goals adopted by the United Nations in 2015. From innovative urban planning to efficient resource management and enhanced community well-being, the book navigates through the multifaceted applications of intelligent systems in the pursuit of sustainable urban development. By emphasizing practical insights, readers gain actionable knowledge to apply the concepts in diverse urban contexts. The authors provide a holistic perspective on the integration of intelligent systems within the context of SDG No. 11. It comprehensively explores the intersection of computing, informatics, and sustainable urban development. Real-world examples and case studies are used to illustrate the successful implementation of intelligent systems in creating sustainable cities. Readers will learn about the integration of computing technologies and informatics in urban environments, aiming to create smarter, resilient, and sustainable cities. With the ever-evolving nature of technology and urban development, this book delves into the latest advancements in intelligent systems, ensuring that readers are equipped with insights into cutting-edge technologies and their potential impact on sustainable cities. A multidimensional approach using ... Unknown localization key: "more"

Objev podobné jako Intelligent Systems of Computing and Informatics in Sustainable Urban Development

In Learning To Lead Computing, Karl McGrath and Allen Tsui provide an essential, jargon-free guide for educators tasked with leading computing at their school. Drawing from over a decade of experience in education, the authors deliver practical advice and strategies to engage and inspire both colleagues and empower them as leaders. This comprehensive handbook offers step-by-step instructions on everything from curriculum sequence to staff motivation, sharing research-backed approaches such as PRIMM and Parsons problems to encourage deeper thinking about computing in the classroom. Karl McGrath and Allen Tsui''s approachable style, ensures that even non-specialists can confidently lead computing education. Ideal for ECTs, computing subject leads and senior leaders, this book transforms complex subjects into engaging and manageable content, empowering educators to foster a generation of tech-savvy digital citizens.

Objev podobné jako Learning to Lead Computing: A guide for teachers and leaders - Allen Tsui, Karl McGrath

No matter what you teach, there is a 100 Ideas title for you!The 100 Ideas series offers teachers practical, easy-to-implement strategies and activities for the classroom. Each author is an expert in their field and is passionate about sharing best practice with their peers.Each title includes at least ten additional extra-creative Bonus Ideas that won''t fail to inspire and engage all learners._______________An essential collection of 100 practical, tried-and-tested ideas for teaching computing in secondary schools. This is the perfect resource for computing teachers at all levels, whether specialist or non-specialist, newly qualified or experienced. From rubber duck debugging to teaching algorithm design through magic tricks and even setting up an escape room to raise awareness about cyber security, this is the ultimate toolkit for any teacher looking to diversify their lesson plans or revamp their teaching of computing. The activities are research-informed and ready to use in Key Stages 3 and 4 classrooms of all abilities, requiring minimum preparation and resources. 100 Ideas for Secondary Teachers: Outstanding Computing Lessons will ignite students’ passion for coding, programming and computational thinking.Additional online resources for the book can be found at www.bloomsbury.com/100-ideas-secondary-computing

Objev podobné jako 100 Ideas for Secondary Teachers: Outstanding Computing Lessons - Simon Johnson

This book investigates in detail the emerging deep learning (DL) technique in computational physics, assessing its promising potential to substitute conventional numerical solvers for calculating the fields in real-time. After good training, the proposed architecture can resolve both the forward computing and the inverse retrieve problems.Pursuing a holistic perspective, the book includes the following areas. The first chapter discusses the basic DL frameworks. Then, the steady heat conduction problem is solved by the classical U-net in Chapter 2, involving both the passive and active cases. Afterwards, the sophisticated heat flux on a curved surface is reconstructed by the presented Conv-LSTM, exhibiting high accuracy and efficiency. Additionally, a physics-informed DL structure along with a nonlinear mapping module are employed to obtain the space/temperature/time-related thermal conductivity via the transient temperature in Chapter 4. Finally, in Chapter 5, a series of the latest advanced frameworks and the corresponding physics applications are introduced.As deep learning techniques are experiencing vigorous development in computational physics, more people desire related reading materials. This book is intended for graduate students, professional practitioners, and researchers who are interested in DL for computational physics.

Objev podobné jako Deep Learning-Based Forward Modeling and Inversion Techniques for Computational Physics Problems - Qiang Ren, Yinpeng Wang

If you''ve been curious about artificial intelligence and machine learning but didn''t know where to start, this is the book you''ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning, 2nd Edition teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math - the book will cover the rest. After an introduction to Python, you''ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models'' performance. You''ll also learn: How to use classic machine learning models like k-Nearest Neighbours, Random Forests, and Support Vector Machines, How neural networks work and how they''re trained, How to use convolutional neural networks, How to develop a successful deep learning model from scratch. You''ll conduct experiments along the way, building to a final case study that incorporates everything you''ve learned. This second edition is thoroughly revised and updated, and adds ... Unknown localization key: "more"

Objev podobné jako Practical Deep Learning, 2nd Edition - Ronald T. Kneusel

Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You''ll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. • Foundational reinforcement learning concepts and methods • The most popular deep reinforcement learning agents solving high-dimensional environments • Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for ... Unknown localization key: "more"

Objev podobné jako Grokking Deep Reinforcement Learning - Miguel Morales

Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch teaches you how to implement deep learning algorithms with Python and PyTorch. This book takes you into a fascinating case study: building an algorithm capable of detecting malignant lung tumors using CT scans. As the authors guide you through this real example, you''ll discover just how effective and fun PyTorch can be. Key features • Using the PyTorch tensor API • Understanding automatic differentiation in PyTorch • Training deep neural networks • Monitoring training and visualizing results • Interoperability with NumPy Audience Written for developers with some knowledge of Python as well as basic linear algebra skills. Some understanding of deep learning will be helpful, however no experience with PyTorch or other deep learning frameworks is required. About the technology PyTorch is a machine learning framework with a strong focus on deep neural networks. Because ... Unknown localization key: "more"

Objev podobné jako Deep Learning with PyTorch - Eli Stevens, Luca Antiga

This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.

Objev podobné jako System Design for Epidemics Using Machine Learning and Deep Learning

Engage the World Change the World Deep Learning has claimed the attention of educators and policymakers around the world. This book not only defines what deep learning is, but takes up the question of how to mobilize complex, whole-system change and transform learning for all students. Deep Learning is a global partnership that works to: transform the role of teachers to that of activators who design experiences that build global competencies using real-life problem solving; and supports schools, districts, and systems to shift practice and how to measure learning in authentic ways. This comprehensive strategy incorporates practical tools and processes to engage students, educators, and families in new partnerships and drive deep learning. Inside you’ll find: The Deep Learning Framework Vignettes and case studies from K-12 classrooms in 1,200 schools in seven countries Guidance for reaching disadvantaged and differently abled students Sample protocols and rubrics for assessment Videos demonstrating deep learning design and innovative leadership in practice Through learning partnerships, learning environments, new pedagogical practices, and leveraged digital skills, deep learning reaches students as never before — preparing them to be active, engaged participants in their future.

Objev podobné jako Deep Learning - Joanne Quinn, Michael Fullan, Joanne J. McEachen

Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. Key features • Structuring problems as Markov Decision Processes • Popular algorithms such Deep Q-Networks, Policy Gradient method and Evolutionary Algorithms and the intuitions that drive them • Applying reinforcement learning algorithms to real-world problems Audience You’ll need intermediate Python skills and a basic understanding of deep learning. About the technology Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior from their own raw sensory input. The system perceives the environment, interprets the results of its past decisions, and uses this information to optimize its behavior for maximum long-term return. Deep reinforcement learning famously contributed to the success of AlphaGo but that’s not all it can do! Alexander Zai is a Machine Learning Engineer at Amazon AI working on ... Unknown localization key: "more"

Objev podobné jako Deep Reinforcement Learning in Action - Alexander Zai, Brandon Brown

NVIDIA''s Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima Anandkumar, Bren Professor, Caltech, and Director of ML Research, NVIDIA "Ekman uses a learning technique that in our experience has proven pivotal to success—asking the reader to think about using DL techniques in practice. His straightforward approach is refreshing, and he permits the reader to dream, just a bit, about where DL may yet take us." -- From the foreword by Dr. Craig Clawson, Director, NVIDIA Deep Learning Institute Deep learning (DL) is a key component of today''s exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to DL. Illuminating both the core concepts and the hands-on programming techniques needed to succeed, this book is ideal for developers, data scientists, analysts, and others--including those with no prior machine learning or statistics experience.After introducing the essential building blocks of deep neural networks, such as artificial neurons and fully connected, convolutional, and recurrent layers, Magnus ... Unknown localization key: "more"

Objev podobné jako Learning Deep Learning - Magnus Ekman

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.

Objev podobné jako The Science of Deep Learning - Iddo Drori

The mathematical paradigms that underlie deep learning typically start out as hard-to-read academic papers, often leaving engineers in the dark about how their models actually function. Math and Architectures of Deep Learning bridges the gap between theory and practice, laying out the math of deep learning side by side with practical implementations in Python and PyTorch. Written by deep learning expert Krishnendu Chaudhury, you''ll peer inside the “black box” to understand how your code is working, and learn to comprehend cutting-edge research you can turn into practical applications. about the technology It''s important to understand how your deep learning models work, both so that you can maintain them efficiently and explain them to other stakeholders. Learning mathematical foundations and neural network architecture can be challenging, but the payoff is big. You''ll be free from blind reliance on pre-packaged DL models and able to build, customize, and re-architect for your specific needs. And when things go wrong, you''ll be glad you can quickly identify and fix problems. about the book Math and Architectures of Deep Learning sets out the foundations of DL in a way that''s both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept ... Unknown localization key: "more"

Objev podobné jako Math and Architectures of Deep Learning - Krishnendu Chaudhury

Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world''s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects'' desired behavior can be reinforced with positive and negative stimuli. When we see how reinforcement learning teaches a simulated robot to walk, we are reminded of how children learn, through playful exploration. Techniques that are inspired by biology and psychology work amazingly well in computers: animal behavior and the structure of the brain as new blueprints for science and engineering. In fact, computers truly seem to possess aspects of human behavior; as such, this field goes to the heart of the dream of artificial intelligence. These research advances have not gone unnoticed by educators. Many universities have begun offering courses ... Unknown localization key: "more"

Objev podobné jako Deep Reinforcement Learning - Aske Plaat

An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion modelsShort, focused chapters progress in complexity, easing students into difficult concepts Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of modelsStreamlined presentation separates critical ideas from background context and extraneous detailMinimal mathematical prerequisites, extensive illustrations, and practice problems make challenging ... Unknown localization key: "more"

Objev podobné jako Understanding Deep Learning - Simon J.D. Prince

Artificial Intelligence is the most exciting technology of the century, and Deep Learning is, quite literally, the “brain” behind the world’s smartest Artificial Intelligence systems out there. Grokking Deep Learning is the perfect place to begin the deep learning journey. Rather than just learning the “black box” API of some library or framework, readers will actually understand how to build these algorithms completely from scratch. Key Features:Build neural networks that can see and understand images Build an A.I. that will learn to defeat you in a classic Atari gameHands-on Learning Written for readers with high school-level math and intermediateprogramming skills. Experience with Calculus is helpful but notrequired. ABOUT THE TECHNOLOGY Deep Learning is a subset of Machine Learning, which is a field dedicated to the study and development of machines that can learn, often with the goal of eventually attaining general artificial intelligence.

Objev podobné jako Grokking Deep Learning - Andrew W Trask

Deep Learning Crash Course goes beyond the basics of machine learning to delve into modern techniques and applications of great interest right now, and whose popularity will only grow in the future. The book covers topics such as generative models (the technology behind deep fakes), self-supervised learning, attention mechanisms (the tech behind ChatGPT), graph neural networks (the tech behind AlphaFold), and deep reinforcement learning (the tech behind AlphaGo). This book bridges the gap between theory and practice, helping readers gain the confidence to apply deep learning in their work.

Objev podobné jako Deep Learning Crash Course - Benjamin Midtvedt, Jesus Pineda, Giovanni Volpe

Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI).This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling.Features:No prior experience of programming is requiredOnline GitHub repository available with codes for readers to practiceCovers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computingFull solutions to exercises are available as Jupyter notebooks on the WebSupport MaterialGitHub Repository of Python Files and Notebooks: https://github.com/proflynch/CRC-Press/Solutions to All Exercises:Section 1: An Introduction to Python: https://drstephenlynch.github.io/webpages/Solutions_Section_1.htmlSection 2: Python for Scientific Computing: ... Unknown localization key: "more"

Objev podobné jako Python for Scientific Computing and Artificial Intelligence - Stephen Lynch

In this book the authors aim to endow the reader with an operational, conceptual, and methodological understanding of the discrete mathematics that can be used to study, understand, and perform computing. They want the reader to understand the elements of computing, rather than just know them. The basic topics are presented in a way that encourages readers to develop their personal way of thinking about mathematics. Many topics are developed at several levels, in a single voice, with sample applications from within the world of computing. Extensive historical and cultural asides emphasize the human side of mathematics and mathematicians.By means of lessons and exercises on "doing" mathematics, the book prepares interested readers to develop new concepts and invent new techniques and technologies that will enhance all aspects of computing. The book will be of value to students, scientists, and engineers engaged in the design and use of computing systems, and to scholars and practitioners beyond these technical fields who want to learn and apply novel computational ideas.

Objev podobné jako Understand Mathematics, Understand Computing - Arnold L. Rosenberg, Denis Trystram

This book is the second part of Applications and Trends in Fintech, which serves as a comprehensive guide to the advanced topics in fintech, including the deep learning and natural language processing algorithms, blockchain design thinking, token economics, cybersecurity, cloud computing and quantum computing, compliance and risk management, and global fintech trends. Readers will gain knowledge about the applications of fintech in finance and its latest developments as well as trends.This fifth volume covers global fintech trends and emerging technologies such as cloud computing and quantum computing, as well as the compliance and risk management frameworks for fintech companies. Together with the first part in applications and trends (fourth volume), these two books will deepen readers'' understanding of the fintech fundamentals covered in previous volumes through various applications and analysis of impacts and trends.Bundle set: Global Fintech Institute-Chartered Fintech Professional Set I

Objev podobné jako Applications And Trends In Fintech Ii: Cloud Computing, Compliance, And Global Fintech Trends

researchED is an educator-led organisation with the goal of bridging the gap between research and practice. This accessible and punchy series, overseen by founder Tom Bennett, tackles the most important topics in education, with a range of experienced contributors exploring the latest evidence and research and how it can apply in a variety of classroom settings. In this edition, Kate Jones considers various principles from cognitive science that can be used to enhance teaching and learning, including cognitive load theory, dual coding theory, interleaving, retrieval practice and spaced practice. Kate has sourced contributions from teachers and researchers including Jade Pearce, Sarah Cottingham, Adam Boxer, Jonathan Firth, Paul A. Kirschner, Pedro De Bruyckere and Lekha Sharma. Kate Jones is a teacher and an experienced leader. She is the author of seven books and is senior associate for teaching and learning at Evidence Based Education.

Objev podobné jako The researchED Guide to Cognitive Science: An evidence-informed guide for teachers - Kate Jones

Help students move from surface-level learning to the transfer of understanding. How do social studies teachers maximize instruction to ensure students are prepared for an informed civic life? VISIBLE LEARNING® for Social Studies, Grades K-12 shows how the field is more than simply memorizing dates and facts—it encapsulates the skillful ability to conduct investigations, analyze sources, place events in historical context, and synthesize divergent points of view. The Visible Learning framework demonstrates that learning is not an event, but rather a process in which students move from surface-level learning to deep learning, and then onto the transfer of concepts, skills, and strategies. Encouraging learners to explore different facets of society, history, geography, and more, best practices for applying visible learning to social studies curriculum are presented through: ·        A scaffolded approach, including surface-level learning, deep learning, and transfer of learning ·        Examples of strategies, lessons, and activities best suited for each level of learning ·        Planning tools, rubrics, and templates to guide instruction Teachers must understand the impact they have on students and select approaches to maximize that impact. ... Unknown localization key: "more"

Objev podobné jako Visible Learning for Social Studies, Grades K-12 - Julie Stern, John Hattie, Douglas Fisher, Nancy Frey

Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch

Objev podobné jako Generative Deep Learning - David Foster

The most human-friendly book on machine learning Somewhere buried in all the systems that drive artificial intelligence, you'll find machine learning—the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point for anyone who wants deeper insight into how all this learning actually happens. This book offers an overview of machine learning and its most important practical applications. Then, you'll dive into the tools, code, and math that make machine learning go—and you'll even get step-by-step instructions for testing it out on your own. For an easy-to-follow introduction to building smart algorithms, this Dummies guide is your go-to. Piece together what machine learning is, what it can do, and what it can't doLearn the basics of machine learning code and how it integrates with large datasetsUnderstand the mathematical principles that AI uses to make itself smarterConsider real-world applications of machine learning and write your own algorithms With clear explanations and hands-on instruction, Machine Learning For Dummies is a great entry-level resource for developers looking to get started with AI and machine learning.

Objev podobné jako Machine Learning For Dummies - John Paul Mueller, Luca Massaron

Selected as the Michigan Council of Teachers of Mathematics winter book club book! Rich tasks, collaborative work, number talks, problem-based learning, direct instruction…with so many possible approaches, how do we know which ones work the best? In Visible Learning for Mathematics, six acclaimed educators assert it’s not about which one—it’s about when—and show you how to design high-impact instruction so all students demonstrate more than a year’s worth of mathematics learning for a year spent in school. That’s a high bar, but with the amazing K-12 framework here, you choose the right approach at the right time, depending upon where learners are within three phases of learning: surface, deep, and transfer. This results in "visible" learning because the effect is tangible. The framework is forged out of current research in mathematics combined with John Hattie’s synthesis of more than 15 years of education research involving 300 million students. Chapter by chapter, and equipped with video clips, planning tools, rubrics, and templates, you get the inside track on which instructional strategies to use at each phase of the learning cycle: Surface learning phase: When—through carefully constructed experiences—students explore new concepts and make connections to procedural skills and vocabulary that give shape ... Unknown localization key: "more"

Objev podobné jako Visible Learning for Mathematics, Grades K-12 - Douglas Fisher, Nancy Frey, John Hattie, Sara Delano Moore, Linda M. Gojak, William Mellman

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics - Peter Gedeck, Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Inbal Yahav

Understand what metacognition is and how you can apply it to your secondary school teaching to support deep and effective learning in your classroom. Metacognition is a popular topic in teaching and learning debates, but it’s rarely clearly defined and can be difficult for teachers to understand how it can be applied in the classroom. This book offers a clear introduction to applying metacognition in secondary teaching, exploring the ‘what’, ‘when/how’ and ‘why’ of using metacognition in classrooms with real life examples of how this works in practice. This is a detailed and accessible resource that offers guidance that teachers can start applying to their own lesson planning immediately, across secondary subjects. Nathan Burns is the founder of @MetacognitionU and has written metacognitive teaching resources for TES and Oxford University Press. He is Head of Maths in a Derbyshire school. Â

Objev podobné jako Inspiring Deep Learning with Metacognition - Nathan Burns

In November 2008, John Hattie’s ground-breaking book Visible Learning synthesised the results of more than fifteen years research involving millions of students and represented the biggest ever collection of evidence-based research into what actually works in schools to improve learning.Visible Learning for Teachers takes the next step and brings those ground breaking concepts to a completely new audience. Written for students, pre-service and in-service teachers, it explains how to apply the principles of Visible Learning to any classroom anywhere in the world. The author offers concise and user-friendly summaries of the most successful interventions and offers practical step-by-step guidance to the successful implementation of visible learning and visible teaching in the classroom.This book:links the biggest ever research project on teaching strategies to practical classroom implementationchampions both teacher and student perspectives and contains step by step guidance including lesson preparation, interpreting learning and feedback during the lesson and post lesson follow upoffers checklists, exercises, case studies and best practice scenarios to assist in raising achievementincludes whole school checklists and advice for school leaders on facilitating visible learning in their institutionnow includes additional meta-analyses bringing the total cited within the research to over 900comprehensively covers numerous areas of learning activity including pupil ... Unknown localization key: "more"

Objev podobné jako Visible Learning for Teachers - John Hattie

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning—also known as data mining or predictive analytics—is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter on deep learningA new chapter on experimental feedback techniques, including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics - Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Kuber R. Deokar

Exam board: SQALevel: HigherSubject: Computing ScienceFirst teaching: August 2018First exams: Summer 2019Trust highly experienced teachers and authors Jane Paterson and John Walsh to guide you through the latest SQA Higher Computing Science specification (for examination from 2019 onwards).This is the most comprehensive resource available for this course, brought to you by Scotland''s No. 1 textbook publisher.- Gain in-depth knowledge of the four areas of study (Software Design and Development, Database Design and Development, Web Design and Development, Computer Systems) with clear explanations of every concept and topic- Understand advanced concepts and processes as numerous examples throughout the book show the theory in action- Build the skills of analysis, design, implementation, testing and evaluation that are required for success in both the exam and the assignment- Apply the knowledge and skills developed through the course to a variety of practical tasks and end-of-chapter ''check your learning'' questions- Use computing terminology confidently and accurately by consulting a detailed glossary of all key terms and acronyms

Objev podobné jako Higher Computing Science - John Walsh, Jane Paterson

Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays a crucial role in predicting the future performance and results of a company. In real-time, data collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets -- choosing an appropriate machine learning model results in accurate analyzing, forecasting the future, and making informed decisions. The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 -- growing at a CAGR of 44.06% between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future research work. The future trends of ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics

Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create ''deep dream'' artwork, or create new stories in the style of their favorite authors.

Objev podobné jako Deep Learning - Andrew Glassner

Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises.This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots;pencil-and-paper and programming exercises;lecture videos, slides, and MATLAB code examples ... Unknown localization key: "more"

Objev podobné jako Learning for Adaptive and Reactive Robot Control - Aude Billard, Sina Mirrazavi

Quality Learning for Positive Ageing explores the views of older adult learners to understand the factors that contribute to ‘quality’ in later-life learning and how these relate to wellbeing, positive ageing, and gaining protection against cognitive decline.Through capturing and considering the viewpoints of learners, facilitators and learning organisations, the author outlines the specific characteristics of quality that they associate with informal learning and how it can be enhanced through the adoption of simple strategies. Key topics covered include the implications of an increasing ageing population and barriers to older people learning as well as the cognitive, mental wellbeing, health, and social benefits of learning in later life. Illustrated throughout with vignettes of real later-life learners, this thought-provoking text unpicks how learners can maximise the benefits of learning in later life for themselves, how tutors can create learning opportunities that embody the characteristics of quality for them, and how providers can offer an environment that simply allows quality learning to flourish.This accessible and comprehensive text will be of great interest to researchers of gerontology and ageing, educational gerontology, adult education, and lifelong learning as well as those engaged in dementia research.

Objev podobné jako Quality Learning for Positive Ageing - Alan Potter

This book explores the purpose, role and function of the university and examines the disconnection between studentsÂ’ approaches to learning and university strategy. It centres on the idea that it is vital to explore what counts as a university in the twenty-first century, what it is for, and for whom, as well as how it can transcend social divisions. The universities of the twenty-first century need to have larger audiences, a broader voice, a shift away from othering and an effective means of progressing such shifts. What is central to such exploration is the idea that learning needs to be seen as postdigital. With a focus on how the growth of technology has and continues to affect university learning, this book:explores the concepts of the digital and the postdigitalpromotes just and inclusive pedagogies for higher educationconsiders ways to ensure learning is an ethical and political experiencestudies how to understand community and collective values through higher educationsuggests ways of promoting personal and collective responsibility for our world and its peoplespresents ways in which the university can challenge ideologies based on capitalist modes of consumption, privilege and exploitationDigital and Postdigital Learning for Changing Universities is essential reading for anyone seeking to reimagine ... Unknown localization key: "more"

Objev podobné jako Digital and Postdigital Learning for Changing Universities - Savin-Baden Maggi

Elektronická kniha - autor François Chollet, 328 stran, česky Strojové učení zaznamenalo v posledních letech pozoruhodný pokrok od téměř nepoužitelného rozpoznávání řeči a obrazu k nadlidské přesnosti. Od programů, které nedokázaly porazit jen trochu zkušenějšího hráče go, jsme dospěli k přemožiteli mistra světa. Za pokrokem ve vývoji učících se programů stojí tzv. hluboké učení (deep learning) – kombinace technických vylepšení, osvědčených postupů a teorií, které umožnily vyvinout množství dříve nerealizovatelných inteligentních aplikací. S jejich pomocí pak můžeme například analyzovat text či mluvené slovo, překládat z jazyka do jazyka, rozpoznávat osoby na sociálních sítích nebo používat samořídící automobily. Tato kniha naučí čtenáře navrhovat hluboce se učící systémy v jazyku Python, který je v současnosti nejpoužívanějším programovacím jazykem pro vývoj těchto systémů, a knihovny Keras a TensorFlow používané většinou vítězů soutěží systémů pro...

Objev podobné jako Deep learning v jazyku Python (978-80-247-3100-1)

Strojové učení zaznamenalo v posledních letech pozoruhodný pokrok a dospělo od téměř nepoužitelného rozpoznávání řeči a obrazu k téměř nadlidské přesnosti, od programů, které nedokázaly porazit jen trochu zkušenějšího hráče šachu, až k přemožitelům mistrů světa.Za pokrokem ve vývoji učících se programů stojí tzv. hluboké učení (deep learning), což je kombinace teorií a osvědčených technických postupů, které umožnily vyvinout řadu dříve nerealizovatelných aplikací. S jejich pomocí můžeme analyzovat a syntetizovat text i mluvené slovo, překládat z jazyka do jazyka, rozpoznávat osoby nebo ovládat samořídící automobily.Kniha naučí čtenáře, jehož znalosti jazyka Python jsou na střední úrovni, navrhovat v tomto jazyku hluboce se učící systémy s pomocí knihoven Keras a TensorFlow, které používá většina autorů vítězných systémů ze soutěží v hlubokém učení. Výklad je založený na intuitivních vysvětleních a praktických příkladech. Náročné koncepty si procvičíte na aplikacích v oblasti počítačového vidění, zpracování přirozeného jazyka a generativních modelů. Získáte tak znalosti a praktické dovednosti, které vám umožní aplikovat hluboké učení ve vlastních projektech.Autorem knihy je François Chollet, tvůrce knihovny Keras a výzkumník v oblasti umělé inteligence společnosti Google. Výklad základních principů hlubokého učení i pokročilých dovedností Tvorba systému hlubokého učení pro počítačové vidění, časové řady, text i generování vlastních výtvorů (například obrázků) Způsob ... Unknown localization key: "more"

Objev podobné jako Deep learning v jazyku Python - 2., rozšířené vydání - François Chollet

This social and emotional learning (SEL) workbook for kindergarten students provides daily activities to learn about emotions, actions, relationships, and decision making.180 Days™: Social-Emotional Learning for KindergartenUses daily activities to promote students’ self-awareness, analyze relationships, discover diverse perspectives, and apply what they have learnedBuilds student''s confidence in self-reflection and growth through the use of fiction and nonfiction textsMakes at-home learning, whole class instruction, or small group support, quick and easyConnections will be made to the CASEL competencies, mindfulness, and key affective education initiativesParents appreciate the teacher-approved activity books that keep their child engaged and learning. Great for homeschooling, to reinforce learning at school, and build connections between home and school.Teachers rely on the daily practice workbooks to save them valuable time. The ready to implement activities are perfect to introduce SEL topics for discussion.

Objev podobné jako 180 Daysâ„¢: Social-Emotional Learning for Kindergarten - Jodene Smith, Brenda A. Van Dixhorn

This book illustrates complex concepts of full stack deep learning and reinforces them through hands-on exercises to arm you with tools and techniques to scale your project.

Objev podobné jako Deep Learning at Scale - Suneeta Mall

Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real world applications. Learning from hands-on case studies, you''ll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. About the Technology Ensemble machine learning lets you make robust predictions without needing the huge datasets and processing power demanded by deep learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results.

Objev podobné jako Ensemble Methods for Machine Learning - Gautam Kunapuli

This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. 2. Domain-sensitive learning and information retrieval: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. 3. Natural language processing: Chapters 10 through 16 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, transformers, pre-trained language models, text summarization, information extraction, knowledge graphs, question answering, opinion mining, text segmentation, and event detection. Compared to the first edition, this second edition textbook (which targets mostly advanced level students majoring in computer science and math) has substantially more material on deep learning and natural language processing. Significant ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Text - Charu C. Aggarwal

Syllabus: CfE (Curriculum for Excellence, from Education Scotland) and SQALevel: BGE S1-3: Third and Fourth LevelsSubject: Computing Science and Digital LiteracyCreate, innovate, solve problems, achieve. Through 30% theory and 70% practical work, pupils are challenged and motivated to develop their skills, knowledge and understanding from S1 to S3.Covering all CfE Third and Fourth Level Benchmarks for Technologies: Computing Science and Digital Literacy, this ready-made and differentiated course puts progression for every pupil at the heart of your curriculum.> Follow a consistent, classroom-tested lesson structure: Each double-page spread provides the learning intentions, key concept explanations and activities for one lesson> Build and apply computational thinking skills: From creating games and coding in Python to designing web pages and databases, pupils will analyse, test and evaluate different software and devices> Meet the needs of each pupil in your class: The content and activities are designed to ensure accessibility for those with low prior attainment, while extension tasks will stretch high achieving pupils> Effectively check and assess progress: ''Work it out'' knowledge-check questions support formative assessment within each lesson, helping you to monitor progression against the Experiences & Outcomes and Benchmarks> Lay firm foundations for National qualifications: The skills, knowledge and understanding established ... Unknown localization key: "more"

Objev podobné jako BGE S1-S3 Computing Science and Digital Literacy: Third and Fourth Levels - David Alford

Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math. The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization. This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.

Objev podobné jako Machine Learning for Managers - Paul Geertsema

This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.•Where is the method applied?•How is the method developed?•How is the method implemented?•How well does the method work?The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.

Objev podobné jako An Introduction to Scientific Computing with MATLAB® and Python Tutorials - Sheng Xu

A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the ... Unknown localization key: "more"

Objev podobné jako Applied Machine Learning for Data Science Practitioners - Vidya Subramanian