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EBookClubs

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Book Learning How to Learn

Download or read book Learning How to Learn written by Barbara Oakley, PhD and published by Penguin. This book was released on 2018-08-07 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.

Book bookdown

    Book Details:
  • Author : Yihui Xie
  • Publisher : CRC Press
  • Release : 2016-12-12
  • ISBN : 1351792601
  • Pages : 140 pages

Download or read book bookdown written by Yihui Xie and published by CRC Press. This book was released on 2016-12-12 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats, including LaTeX/PDF, HTML, EPUB, and Word, thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book, but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers, reports, dissertations, course handouts, study notes, and even novels. You do not have to use R, either. Other choices of computing languages include Python, C, C++, SQL, Bash, Stan, JavaScript, and so on, although R is best supported. You can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub.

Book Beyond the Basic Stuff with Python

Download or read book Beyond the Basic Stuff with Python written by Al Sweigart and published by No Starch Press. This book was released on 2020-12-16 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: BRIDGE THE GAP BETWEEN NOVICE AND PROFESSIONAL You've completed a basic Python programming tutorial or finished Al Sweigart's bestseller, Automate the Boring Stuff with Python. What's the next step toward becoming a capable, confident software developer? Welcome to Beyond the Basic Stuff with Python. More than a mere collection of advanced syntax and masterful tips for writing clean code, you'll learn how to advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control. Sweigart takes you through best practices for setting up your development environment, naming variables, and improving readability, then tackles documentation, organization and performance measurement, as well as object-oriented design and the Big-O algorithm analysis commonly used in coding interviews. The skills you learn will boost your ability to program--not just in Python but in any language. You'll learn: Coding style, and how to use Python's Black auto-formatting tool for cleaner code Common sources of bugs, and how to detect them with static analyzers How to structure the files in your code projects with the Cookiecutter template tool Functional programming techniques like lambda and higher-order functions How to profile the speed of your code with Python's built-in timeit and cProfile modules The computer science behind Big-O algorithm analysis How to make your comments and docstrings informative, and how often to write them How to create classes in object-oriented programming, and why they're used to organize code Toward the end of the book you'll read a detailed source-code breakdown of two classic command-line games, the Tower of Hanoi (a logic puzzle) and Four-in-a-Row (a two-player tile-dropping game), and a breakdown of how their code follows the book's best practices. You'll test your skills by implementing the program yourself. Of course, no single book can make you a professional software developer. But Beyond the Basic Stuff with Python will get you further down that path and make you a better programmer, as you learn to write readable code that's easy to debug and perfectly Pythonic Requirements: Covers Python 3.6 and higher

Book Learn Like a Pro

    Book Details:
  • Author : Barbara Oakley PhD
  • Publisher : St. Martin's Essentials
  • Release : 2021-06-01
  • ISBN : 1250799384
  • Pages : 128 pages

Download or read book Learn Like a Pro written by Barbara Oakley PhD and published by St. Martin's Essentials. This book was released on 2021-06-01 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: A book for learners of all ages containing the best and most updated advice on learning from neuroscience and cognitive psychology. Do you spend too much time learning with disappointing results? Do you find it difficult to remember what you read? Do you put off studying because it’s boring and you’re easily distracted? This book is for you. Dr. Barbara Oakley and Olav Schewe have both struggled in the past with their learning. But they have found techniques to help them master any material. Building on insights from neuroscience and cognitive psychology, they give you a crash course to improve your ability to learn, no matter what the subject is. Through their decades of writing, teaching, and research on learning, the authors have developed deep connections with experts from a vast array of disciplines. And it’s all honed with feedback from thousands of students who have themselves gone through the trenches of learning. Successful learners gradually add tools and techniques to their mental toolbox, and they think critically about their learning to determine when and how to best use their mental tools. That allows these learners to make the best use of their brains, whether those brains seem “naturally” geared toward learning or not. This book will teach you how you can do the same.

Book Emerging Research in Intelligent Systems

Download or read book Emerging Research in Intelligent Systems written by Miguel Botto-Tobar and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the XVI Multidisciplinary International Congress on Science and Technology (CIT 2021), held in Quito, Ecuador, on June 14-18, 2021, proudly organized by Universidad de las Fuerzas Armadas ESPE in collaboration with GDEON. CIT is an international event with a multidisciplinary approach that promotes the dissemination of advances in science and technology research through the presentation of keynote conferences. In CIT, theoretical, technical, or application works that are research products are presented to discuss and debate ideas, experiences, and challenges. Presenting high-quality, peer-reviewed papers, the book discusses the following topics: Artificial Intelligence Computational Modeling Data Communications Defense Engineering Innovation, Technology, and Society Managing Technology & Sustained Innovation, and Business Development Security and Cryptography Software Engineering.

Book Python Machine Learning

    Book Details:
  • Author : Sebastian Raschka
  • Publisher : Packt Publishing Ltd
  • Release : 2015-09-23
  • ISBN : 1783555149
  • Pages : 455 pages

Download or read book Python Machine Learning written by Sebastian Raschka and published by Packt Publishing Ltd. This book was released on 2015-09-23 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Book Phosphorus in Environmental Technology

Download or read book Phosphorus in Environmental Technology written by E. Valsami-Jones and published by IWA Publishing. This book was released on 2004-05-31 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: Phosphorus in Environmental Technology: Principles and Applications, provides a definitive and detailed presentation of state-of-the-art knowledge on the environmental behaviour of phosphorus and its applications to the treatment of waters and soils. Special attention is given to phosphorus removal for recovery technologies, a concept that has emerged over the past 5-6 years. The book features an all-encompassing approach: the fundamental science of phosphorus (chemistry, geochemistry, mineralogy, biology), key aspects of its environmental behaviour and mobility, industrial applications (treatment, removal, recovery) and the principles behind such applications, novel biotechnologies and, importantly, it also addresses socio-economic issues which often influence implementation and the ultimate success of any new technology. A detailed subject index helps the reader to find their way through the different scientific and technological aspects covered, making it an invaluable reference work for students, professionals and consultants dealing with phosphorus-related environmental technologies. State-of-the-art knowledge on the behaviour of phosphorus and its applications to environmental science and technology. Covers all aspects of phosphorus in the environment, engineered and biological systems; an interdisciplinary text.

Book Applied Predictive Modeling

    Book Details:
  • Author : Max Kuhn
  • Publisher : Springer Science & Business Media
  • Release : 2013-05-17
  • ISBN : 1461468493
  • Pages : 595 pages

Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Book For the Win

    Book Details:
  • Author : Kevin Werbach
  • Publisher : Wharton School Press
  • Release : 2012
  • ISBN : 9781613630235
  • Pages : 0 pages

Download or read book For the Win written by Kevin Werbach and published by Wharton School Press. This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Millions play Farmville, Scrabble, and countless other games, generating billions in sales each year. The careful and skillful construction of these games is built on decades of research into human motivation and psychology: A well-designed game goes right to the motivational heart of the human psyche. In For the Win, Kevin Werbach and Dan Hunter argue persuasively that game-makers need not be the only ones benefiting from game design. Werbach and Hunter, lawyers and World of Warcraft players, created the world's first course on gamification at the Wharton School. In their book, they reveal how game thinking--addressing problems like a game designer--can motivate employees and customers and create engaging experiences that can transform your business. For the Win reveals how a wide range of companies are successfully using game thinking. It also offers an explanation of when gamifying makes the most sense and a 6-step framework for using games for marketing, productivity enhancement, innovation, employee motivation, customer engagement, and more.

Book Deep Learning

    Book Details:
  • Author : Josh Patterson
  • Publisher : "O'Reilly Media, Inc."
  • Release : 2017-07-28
  • ISBN : 1491914211
  • Pages : 550 pages

Download or read book Deep Learning written by Josh Patterson and published by "O'Reilly Media, Inc.". This book was released on 2017-07-28 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop

Book The Elements of Statistical Learning

Download or read book The Elements of Statistical Learning written by Trevor Hastie and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Book Autonomous Systems  Developments and Trends

Download or read book Autonomous Systems Developments and Trends written by Herwig Unger and published by Springer Science & Business Media. This book was released on 2011-10-30 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Workshops on Autonomous Systems emanated from a gathering with the doctoral students of just three chairs at Fernuniversität in Hagen, which we organise twice per year for a number of years now. Their purpose is to discuss on-going research and to create a community spirit. Furthermore, they serve as a means of structuring the students' research processes. The workshop has grown and matured in several respects. The doctoral students presenting their work do not come from a single university anymore, but from three. Besides them and their supervisors, also other scientists became interested in the event and contribute to its programme. Following the model of Advanced Study Institutes, they are available on the premises for relaxed, informal discussions outside the formal sessions. Finally, with the co-sponsorship of Gesellschaft für Informatik, the German Computer Society, and this surprisingly comprehensive volume of contributions published by Springer-Verlag the workshop turned into a visible scientific event.

Book Hands on Computer Vision with TensorFlow 2

Download or read book Hands on Computer Vision with TensorFlow 2 written by Benjamin Planche and published by . This book was released on 2019 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is achieving a new frontier of capabilities in fields like health, automobile or robotics. This book explores TensorFlow 2, Google's open-source AI framework, and teaches how to leverage deep neural networks for visual tasks. It will help you acquire the insight and skills to be a part of the exciting advances in computer vision.

Book Human Centered Data Science

Download or read book Human Centered Data Science written by Cecilia Aragon and published by MIT Press. This book was released on 2022-03-01 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets. Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow—and show how a human-centered approach can enhance each one, by making the process more transparent, asking questions, and considering the social context of the data. They describe how tools from social science might be incorporated into data science practices, discuss different types of collaboration, and consider data storytelling through visualization. The book shows that data science practitioners can build rigorous and ethical algorithms and design projects that use cutting-edge computational tools and address social concerns.

Book Global Sport Business

    Book Details:
  • Author : Brenda G. Pitts
  • Publisher : Routledge
  • Release : 2020-12-18
  • ISBN : 9780367671594
  • Pages : 316 pages

Download or read book Global Sport Business written by Brenda G. Pitts and published by Routledge. This book was released on 2020-12-18 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the global sport business industry, growth, and development within and across various sport businesses are essential for competitive advantage. This fascinating collection of chapters examines how the development and management of resources and opportunities in sport business is vital to success. Commissioned by the World Association for Sport Management (WASM) and featuring global perspectives from leading international scholars and original research data drawn from both qualitative and quantitative inquiry, the book presents cases as diverse as customer demand in the NBA, sport and physical activity human resources in Spain and stakeholder relationships in Chinese football. Presented in three parts (global perspectives, managing resources, and managing opportunities), Global Sport Business examines key research and practical issues in sport business management and marketing studies in both global and local contexts. This is an important read for professors, scholars, and students in sport business management, a useful resource for sport business management professionals and practitioners, and illuminating reading for anyone with an interest in sport management.

Book Computer Age Statistical Inference

Download or read book Computer Age Statistical Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2016-07-21 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Book How Humans Judge Machines

Download or read book How Humans Judge Machines written by Cesar A. Hidalgo and published by MIT Press. This book was released on 2021-02-02 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: How people judge humans and machines differently, in scenarios involving natural disasters, labor displacement, policing, privacy, algorithmic bias, and more. How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance? How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions. Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender? César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer tounderstanding the ethical consequences of AI.