Influence Human Behavior: The Ultimate Guide to Learning the New Science Driving the Big Change, How to Win Friends and Influence People in Priv Independently Published

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Have you ever met people who have the ability to influence others to do anything they want? Chances are you have been a victim of such people, who made you do something for them even when you did not approve of what they were asking, and l

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New Science of Learning Stylus Publishing

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The Science of Interpersonal Relations: A Practical Guide to Building Healthy Relationships, Improving Your Soft Skills and Learning Effective Communi Createspace Independent Publishing Platform

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From first dates and successful relationships to friends, colleagues, and new acquaintances, unlock the hidden secrets to successful communication with anyone and learn to flourish in any environment. **MY GIFT TO YOU INSIDE: Link to download

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Learning and Teaching Primary Science Cambridge University Press

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Learning and Teaching Primary Science brings primary science to life through the stories and experiences of pre-service and practising teachers. It explores the roles of the teacher and the learner of science and examines major issues and challenges, including: engaging diverse learners, utilising technology, assessment and reporting, language and representation, and integration in the 'crowded curriculum'. Each chapter contains examples, activities and reflective questions to help readers create relevant and meaningful lesson plans. Dedicated chapters for the areas of chemistry, physics, biology and earth and environmental science will give confidence to those without a science background. Practical strategies and skills are underpinned by relevant theories and evidence-based research. Written by experts from Australia and New Zealand, Learning and Teaching Primary Science is an essential resource for those beginning their journey of teaching science in the primary school classroom.

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Practical Machine Learning: A New Look At Anomaly Detection

Książki Obcojęzyczne>Angielskie>Computing & information technology>Computer science

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Deep Learning for Physical Scientists - Accelerating Research with Machine Learning John Wiley and Sons Ltd

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Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the fieldDeep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep learning within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome.Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems. Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader.From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy:* A thorough introduction to the basic classification and regression with perceptrons* An exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of training* An examination of multi-layer perceptrons for learning from descriptors and de-noising data* Discussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from images* A treatment of Bayesian optimization for tuning deep learning architecturesPerfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access. This book introduces the reader to the transformative techniques involved in deep learning. A range of methodologies are addressed including: *Basic classification and regression with perceptrons *Training algorithms, such as back propagation and stochastic gradient descent and the parallelization of training *Multi-Layer Perceptrons for learning from descriptors, and de-noising data *Recurrent neural networks for learning from sequences *Convolutional neural networks for learning from images *Bayesian optimization for tuning deep learning architectures Each of these areas has direct application to physical science research, and by the end of the book, the reader should feel comfortable enough to select the methodology which is best for their situation, and be able to implement and interpret outcome of the deep learning model. The book is designed to teach researchers to think in new ways, providing them with new avenues to attack problems, and avoid roadblocks within their research. This is achieved through the inclusion of case-study like problems at the end of each chapter, which will give the reader a chance to practice what they have just learnt in a close-to-real-world setting, with example 'solutions' provided through an online resource. Market Description This book introduces the reader to the transformative techniques involved in deep learning. A range of methodologies are addressed including: * Basic classification and regression with perceptrons * Training algorithms, such as back propagation and stochastic gradient descent and the parallelization of training * Multi-Layer Perceptrons for learning from descriptors, and de-noising data * Recurrent neural networks for le

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Learning About Learning Disabilities Elsevier Science Publishing Co Inc

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Learning about Learning Disabilities, 4e continues to provide equal attention to the intellectual, conceptual, and practical aspects of learning disabilities. The Fourth Edition of this popular title presents 80% new material, keeping the chapters up to date in this fast-moving field. With new contributors, and 11 new chapters, coverage is both comprehensive and thorough, encompassing the classification and identification of learning disabilities, learning disabilities in reading, writing, math, and social studies, interventions, and the issues germane to different age ranges of the learning disabled: children, adolescents, and adults. Readers will find Learning About Learning Disabilities, Fourth Edition suitable for use as a reference source for researchers or as a graduate level text.§Reviews of previous editions:§"This text provides a balanced focus on both the conceptual and practical aspects of learning disabilities. Its research coverage is more comprehensive and of greater depth than any other LD textbook, and it is distinctive in its treatment of such important areas as consultation skills and service delivery." -CHILD ASSESSMENT NEWS " ... provides a broad overview of some important issues in relation to the education and development of pupils with learning disabilities... Wong has succeeded in providing detailed descriptions and comments within a book which covers a broad range of topics. Without exception the chapters are clearly written and accessible, and many provide the reader with challenging ideas and practical suggestions." -BRITISH JOURNAL OF SPECIAL EDUCATION§Learning Disabilities occur in 20% of the population. Three million children in the US have a learning disability and receive special education in school. §30% of children with learning disabilities drop out of high school, and 48% of those with learning disabilities are out of the workforce or unemployed. §Discusses different types of learning disabilities including problems with attention, memory, language, math, reading, and writing §Encompasses the impact of LD on learning as well as social competence and self-regulation §Provides research summaries on most effective ways to teach children with LD §Encompasses a lifespan perspective on LD, discussing the impact on children, adolescents, and adults

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The Science of Rapid Skill Acquisition: Advanced Methods to Learn, Remember, and Master New Skills, Information, and Abilities Createspace Independent Publishing Platform

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Scientific Methods to accelerate your learning to save time, beat competition, and get from Point A to point B at the speed of light.Learning is the key to bettering your circumstances and becoming the person you want to be. Skills, information, and abilit

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Exploratorium Science Snackbook - Cook Up Over 100 Hands-On Science Exhibits from Everyday Materials, Revised Edition John Wiley & Sons Inc

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Kids and teachers can build their own science projects based on exhibits from San Francisco's premiere science museum This revised and updated edition offers instructions for building junior versions, or "snacks," of the famed Exploratorium's exhibits. The snacks, designed by science teachers, can be used as demonstrations, labs, or as student science projects and all 100 projects are easy to build from common materials. The Exploratorium, a renowned hands-on science museum founded by physicist and educator Frank Oppenheimer, is noted for its interactive exhibits that richly illustrate scientific concepts and stimulate learning.* Offers a step-by-step guide for building dynamic science projects and exhibits* Includes tips for creating projects made from easy-to-assembly items* Thoroughly revised and updated, including new "snacks," images, and references

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Machine Learning Control by Symbolic Regression Springer, Berlin

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This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and application of numerical methods of symbolic regression to solving control problems, the authors offer new possibilities not only in the field of control automation, but also in the design of completely different optimal structures in many fields. For specialists in the field of control, Machine Learning Control by Symbolic Regression opens up a new promising direction of research and acquaints scientists with the methods of automatic construction of control systems.For specialists in the field of machine learning, the book opens up a new, much broader direction than neural networks: methods of symbolic regression. This book makes it easy to master this new area in machine learning and apply this approach everywhere neural networks are used. For mathematicians, the book opens up a new approach to the construction of numerical methods for obtaining analytical solutions to unsolvable problems; for example, numerical analytical solutions of algebraic equations, differential equations, non-trivial integrals, etc. For specialists in the field of artificial intelligence, the book offers a machine way to solve problems, framed in the form of analytical relationships.

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E-learning Theory and Practice SAGE Publications Ltd

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In E-learning Theory and Practice the authors set out different perspectives on e-learning. The book deals with the social implications of e-learning, its transformative effects, and the social and technical interplay that supports and directs e-learning. The authors present new perspectives on the subject by: - exploring the way teaching and learning are changing with the presence of the Internet and participatory media - providing a theoretical grounding in new learning practices from education, communication and information science - addressing e-learning in terms of existing learning theories, emerging online learning theories, new literacies, social networks, social worlds, community and virtual communities, and online resources - emphasising the impact of everyday electronic practices on learning, literacy and the classroom, locally and globally. This book is for everyone involved in e-learning. Teachers and educators will gain an understanding of new learning practices, and learners will gain a sense of their new role as active participants in classroom and lifelong learning.Graduate students and researchers will gain insight into the direction of research in this new and exciting area of education and the Internet.

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Learning to Program with MATLAB - Building GUI Tools, Second Edition John Wiley and Sons Ltd

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Learning to Program with MATLABIntroductory text integrating science, mathematics, and engineering to give a basic understanding of the fundamentals of computer programming with MATLABLearning to Program with MATLAB: Building GUI Tools, Second Edition serves as a compact introduction to computer programming using the MATLAB language, covering elements of both program and graphical user interface (GUI) design to enable readers to create computer programs just like the ones they are accustomed to interacting with. Rather than being encyclopedic in scope, the goal of the text is to describe what users will find most useful and point to other features. Descriptions and examples of some of the most useful functions are included throughout, particularly with regards to engineering and science applications. The work also includes updated videos and problem solutions on an instructor companion website.The first edition of Learning to Program with MATLAB employed the MATLAB graphical user interface design environment (GUIDE) to develop the GUI tools. The second edition is based on the new and improved App Designer program, which has supplanted GUIDE. This edition includes:* Core concepts of computer programming using MATLAB, such as arrays, loops, functions, and basic data structures* How to write your own MATLAB functions, covering topics such as local workspaces, multiple outputs, function files, and other functional forms* The new string class and table class, some new features of function arguments, and re-written sections for building GUI tools with App Designer* Syntax for graphics and App Designer features, plus examples demonstrating the new way to handle string informationStarting with the basics and building up to an emphasis on GUI tools, Learning to Program with MATLAB is a comprehensive introduction to programming in a robust and multipurpose language, making it an ideal classroom resource for both students and instructors in related programs of study.

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Pattern Recognition and Machine Learning Springer-Verlag New York Inc.

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The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.This completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra isrequired, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher. The book is supported by a great deal of additional material, and the reader is encouraged to visit the book web site for the latest information.Coming soon: For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text) For instructors, worked solutions to remaining exercises from the Springer web site Lecture slides to accompany each chapter Data sets available for download

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Fifth Discipline: The art and practice of the learning organization Cornerstone

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Peter Senge, founder and director of the Society for Organisational Learning and senior lecturer at MIT, has found the means of creating a 'learning organisation'. In The Fifth Discipline, he draws the blueprints for an organisation where people expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nutured, where collective aspiration is set free, and where people are contually learning together. The Fifth Discipline fuses these features together into a coherent body of theory and practice, making the whole of an organisation more effective than the sum of its parts. Mastering the disciplines will: *Reignite the spark of learning, driven by people focused on what truly matters to them. *Bridge teamwork into macro-creativity. *Free you from confining assumptions and mind-sets. *Teach you to see the forest and the trees. *End the struggle between work and family time. The Fifth Discipline is a remarkable book that draws on science, spiritual values, psychology, the cutting edge of management thought and Senge's work with leading companies which employ Fifth Discipline methods.Reading it provides a searching personal experience and a dramatic professional shift of mind. This edition contains more than 100 pages of new material about how companies are actually using and benefiting from Fifth Discipline practices, as well as a new foreword from Peter Senge about his work with the Fifth Discipline over the last 15 years.

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Guide to Deep Learning Basics Springer, Berlin

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This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this exciting field, including the pioneering work of Rudolf Carnap, Warren McCulloch, Walter Pitts, Bulcsú László, and Geoffrey Hinton. Topics and features: Provides a brief history of mathematical logic, and discusses the critical role of philosophy, psychology, and neuroscience in the history of AI Presents a philosophical case for the use of fuzzy logic approaches in AI Investigates the similarities and differences between the Word2vec word embedding algorithm, and the ideas of Wittgenstein and Firth on linguistics Examines how developments in machine learning provide insights into the philosophical challenge of justifying inductive inferences Debates, with reference to philosophical anthropology, whether an advanced general artificial intelligence might be considered as a living being Investigates the issue of computational complexity through deep-learning strategies for understanding AI-complete problems and developing strong AI Explores philosophical questions at the intersection of AI and transhumanism This inspirational volume will rekindle a passion for deep learning in those already experienced in coding and studying this discipline, and provide a philosophical big-picture perspective for those new to the field.

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