practical deep learning for cloud and mobile anirudh koul siddha ganju meher kasam

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

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

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

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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

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

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

Exam Board: CCEALevel: GCSESubject: Learning for LifeFirst Teaching: September 2017First Exam: June 2019Enable students to critically engage with the new content and assessment requirements with this fully updated edition of the market-leading Student''s Book for CCEA GCSE Learning for Life and Work- Provides complete coverage of the new content and assessment requirements with support at every stage from experienced teachers and subject experts David McVeigh, Michaella McAllister and Amanda McAleer- Prepares students for assessment with skills-building activities, practice questions and structured guidance on how to approach questions successfully- Helps engage students through accessible diagrams, research activities and a bank of up-to-date case study material- Develops subject knowledge through clear and detailed coverage of the key content structured around the specification

Objev podobné jako CCEA GCSE Learning for Life and Work Second Edition - Amanda McAleer, Michaella McAllister, Joanne McDonnell

Exam board: CCEALevel: GCSESubject: CitizenshipFirst teaching: September 2017First exams: Summer 2019Target success in CCEA GCSE Learning for Life and Work with this proven formula for effective, structured revision; key content coverage is combined with exam-style tasks and practical tips to create a revision guide that students can rely on to review, strengthen and test their knowledge.With My Revision Notes, every student can:- Plan and manage a successful revision programme using the topic-by-topic planner- Consolidate subject knowledge by working through clear and focused content coverage- Test understanding and identify areas for improvement with regular ''Now Test Yourself'' tasks and answers- Improve exam technique through practice questions and expert tips- Get exam ready with answers to the practice questions available online

Objev podobné jako My Revision Notes: CCEA GCSE Learning for Life and Work: Second Edition - Joanne McDonnell

By moving away from flawed statistical methodologies, you'll move toward an intuitive view of probability as a mathematically rigorous statistical framework that quantifies uncertainty holistically and successfully. This book shows you how.

Objev podobné jako Probabilistic Machine Learning for Finance and Investing - Deepak K. Kanungo

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

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

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

Gamepad pro PC, Xbox Series X|S, Xbox One a Mobilní telefon, kompatibilní se systémem Android, Windows 10, bezdrátové připojení, USB-C (na ovladači), integrovaná baterie, vibrace, analogové páčky, uživatelské mapování tlačítek, černá barva Toužíte po změně, protože se vám omrzelo ovládání PC her s myší a klávesnicí? Už nemusíte hledat. Gamepad PowerA MOGA XP-ULTRA - Wireless Cloud Gaming Controller for Xbox, PC and Mobile je dokonalý prostředek k snadnému ovládání her na PC, Xbox Series X|S, Xbox One a Mobilní telefon. Zážitek ze hry zintenzivní i Vibrace, Analogové páčky a Uživatelské mapování tlačítek. Analogové páčky pomáhají k perfektnímu ovládání pohybu postav ve střílečkách. Černá barva gamepadu a povedené zpracování s ohromující výdrží přepínačů opravdu nadchnou každého skutečného fanoušek her. Nejpodstatnější vychytávky herního ovladače PowerA MOGA XP-ULTRA - Wireless Cloud Gaming Controller for Xbox, PC and Mobile Provedení bez překážejících kabelů vás...

Objev podobné jako PowerA MOGA XP-ULTRA - Wireless Cloud Gaming Controller for Xbox, PC and Mobile (1526788-01)

In just a few years, deep reinforcement learning (DRL) systems such as DeepMinds DQN have yielded remarkable results. This hybrid approach to machine learning shares many similarities with human learning: its unsupervised self-learning, self-discovery of strategies, usage of memory, balance of exploration and exploitation, and its exceptional flexibility. Exciting in its own right, DRL may presage even more remarkable advances in general artificial intelligence. Deep Reinforcement Learning in Python: A Hands-On Introduction is the fastest and most accessible way to get started with DRL. The authors teach through practical hands-on examples presented with their advanced OpenAI Lab framework. While providing a solid theoretical overview, they emphasize building intuition for the theory, rather than a deep mathematical treatment of results. Coverage includes: Components of an RL system, including environment and agents Value-based algorithms: SARSA, Q-learning and extensions, offline learning Policy-based algorithms: REINFORCE and extensions; comparisons with value-based techniques Combined methods: Actor-Critic and extensions; scalability through async methods Agent evaluation Advanced and experimental techniques, and more How to achieve breakthrough machine learning performance by combining deep neural networks with reinforcement learning Reduces the learning curve by relying on the authors’ OpenAI Lab framework: requires less upfront theory, math, and programming expertise Provides ... Unknown localization key: "more"

Objev podobné jako Foundations of Deep Reinforcement Learning - Laura Graesser, Wah Loon Keng

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

First, let’s commend ourselves: how in the midst of a pandemic we faculty stepped up at record speed to teach in such a foreign learning environment. Try we did, adapt we did, and learn we did. But to be clear, and we already recognize this, this past spring was less about distance learning and more about crisis teaching. This time around we have the opportunity to be much more purposeful and intentional, and that’s where The Distance Learning Playbook for College and University Instruction will prove absolutely indispensable. Much more than a collection of cool tools and apps, The Distance Learning Playbook for College and University Instruction mobilizes decades of Visible Learning® research to reveal those evidence-based strategies that work best in an online environment. Supplemented by video footage and opportunities to self-assess and reflect, the book addresses every dynamic that must be in place for students to learn, even at a distance: Faculty-student relationships from a distance  Teacher credibility from a distance Teacher clarity from a distance Engaging tasks from a distance Planning learning experiences from a distance Feedback, assessment, and grading from a distance Keeping the focus on learning, from a distance or otherwise What does our ... Unknown localization key: "more"

Objev podobné jako The Distance Learning Playbook for College and University Instruction - Douglas Fisher, Nancy Frey, John Hattie, John T. Almarode

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

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

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

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

An accessible, practical and up-to-date book on digital learning and teaching, relevant for all those involved in teaching and assessment in higher and further education (HE and FE), whatever your academic or vocational specialism. Fully supports learners in developing skills for the new Diploma in Teaching (Further Education and Skills) qualification . It is essential reading for HE or FE practitioners, or those undertaking level 3, 4 and 5 qualifications in Education and Training, Postgraduate Certificates in Education (PGCEs), Certificates in Education (CertEds) and Postgraduate Certificates in Academic Practice (PGCAPs), as well as those in learning technologist roles. The impact of the Covid-19 pandemic has highlighted the importance of understanding and developing your digital capabilities as a basic competence in order to embrace current digital technologies and pedagogies to improve student outcomes. This book provides you with the practical knowledge and skills required to source and apply technology enhanced learning, teaching and assessment (TELTA) and adapt traditional learning and teaching materials and approaches for an online environment. It is designed around each aspect of the teaching and training cycle – identifying needs, planning and designing, delivering and facilitating, assessing and evaluating – and also includes: • how to build a ... Unknown localization key: "more"

Objev podobné jako Digital Learning, Teaching and Assessment for HE and FE Practitioners - Daniel Scott

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

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

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively.Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders.Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.

Objev podobné jako Data Science and Machine Learning for Non-Programmers - Dothang Truong

The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field.It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application domains. It demonstrates the fundamental techniques involved in data collection, integration, cleansing, transformation, development, and deployment of machine learning models. This book emphasizes the importance of integrating responsible and explainable AI into machine learning models, ensuring these principles are prioritized rather than treated as an afterthought. To support learning, this book also offers information on accessing additional machine learning resources such as datasets, libraries, pre-trained models, and tools for tracking machine learning models.This is a core resource for students and instructors of machine learning and data science looking for beginner-friendly material which offers real-world applications and takes ethical discussions into account.

Objev podobné jako Practical Machine Learning - Ally S. Nyamawe, Salim A. Diwani, Noe E. Nnko, Mohamedi M. Mjahidi, Kulwa Malyango, Godbless G. Minja

Perhaps the biggest factor influencing teacher wellbeing and student learning is whether students are calm, focussed, and attentive in the classroom. Despite this, most teachers feel that their teacher training allocated far too little time to the fundamental principles and practical strategies that form the foundation of effective classroom management. In this book, Mark Dowley and Ollie Lovell address this shortfall by revealing 10 principles and 18 routines that will set you up for classroom management success. The Classroom Management Handbook, is the most concise, scaffolded, and unapologetically practical guide to classroom management available.

Objev podobné jako The Classroom Management Handbook: A practical blueprint for engagement and behaviour in your classroom and beyond - Oliver Lovell, Dr. Mark Dowley

Research Methods: A Practical Guide for Students and Researchers is a practical guide on how to conduct research systematically and professionally. The book begins by distinguishing between causal and interpretive sciences. It then guides the reader on how to formulate the research question, review the literature, develop the hypothesis or framework, select a suitable research methodology, and analyze both quantitative and qualitative data.The book uses classic examples as exemplars. It also uses many examples from different disciplines and sectors to demonstrate and showcase the inter-connections and wider applications of research tools.The book emphasizes integration. It does not merely provide a smorgasbord of research designs, data collection methods, and ways to analyze data. Instead, it shows how one could formulate research strategies given the outcomes the researchers are required or tasked to deliver.The revised edition includes three new chapters on time series (including spatial models), machine learning, and meta-analysis. In addition, existing chapters have been expanded to include more examples, digital research, and new material.

Objev podobné jako Research Methods: A Practical Guide For Students And Researchers - Willie Tan

Cestovní GaN adaptér s celkovým výkonem 65W nabízí 3× USB-C a 2× USB-A porty. Obsahuje tři výměnné zástrčky pro použití v EU, UK a USA/AUS. Díky GaN technologii má kompaktní rozměry vhodné pro cestování.

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Objev podobné jako FIXED Travel GaN Adapter EU UK USA/AUS s 3xUSB-C a 2xUSB výstupem PD 65W bílý (FIXCT65-3C2A-WH)

Rainy days are lots of fun when you have a friend to show you how to play fair - a story for toddlers about empathy and the environment with a surprise rainbow pop-up. From the winner of the Laugh Out Loud Book Award (Lollies) 2023 and the Waterstones Children's Book Prize 2014Rabbit is going fishing, but it's raining and he does NOT like getting wet. So, he squeeeezes the rain cloud into his bag - now the rain can't spoil his day! Duck loves the rain, and he sets out to show that bossy bunny how important it is for plants, rivers and the crunchy carrots Rabbit so likes to eat. Can he convince Rabbit to see the sunny side of soggy days and set the cloud free?Join Rabbit and Duck for a fun story with an environmental message and about the importance of rain in the natural world and seeing things from other points of view. Includes a FREE Nosy Crow Stories Aloud® audiobook! Scan the code, hear the story.

Objev podobné jako The Rabbit, the Cloud and the Rainy Day - O'Byrne Nicola

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

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

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

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

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

This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.

Objev podobné jako Machine Learning for Computer Scientists and Data Analysts - Houman Homayoun, Zhiqian Chen, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao

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

Written by more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets, and explores connections with data science and more traditional approaches. This is an invaluable resource for researchers and graduate students in financial engineering, as well as practitioners in the sector.

Objev podobné jako Machine Learning and Data Sciences for Financial Markets

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

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

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

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of "black-box" in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications.This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making.This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially ... Unknown localization key: "more"

Objev podobné jako Human and Machine Learning