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| Author | : Diana Noonan |
| Publisher | : Teacher Created Materials |
| Total Pages | : 34 |
| Release | : 2024-02-13 |
| Genre | : Juvenile Nonfiction |
| ISBN | : |
There are many different jobs in which people make predictions for the future based on data collected in the past. Volcanologists and seismologists use data collection to make predictions for the future based on data collected in the past! With vibrant ph
| Author | : Diana Noonan |
| Publisher | : Teacher Created Materials |
| Total Pages | : 34 |
| Release | : 2024-02-13 |
| Genre | : Juvenile Nonfiction |
| ISBN | : |
With this engaging book, students will learn about the importance of predicting and estimating in relation to natural disasters such as hurricanes, tornadoes, and tsunamis. Charts and data are provided so that students can learn how scientists make predic
| Author | : Martin Kleppmann |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 658 |
| Release | : 2017-03-16 |
| Genre | : Computers |
| ISBN | : 1491903104 |
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
| Author | : Eric Siegel |
| Publisher | : John Wiley & Sons |
| Total Pages | : 368 |
| Release | : 2016-01-12 |
| Genre | : Business & Economics |
| ISBN | : 1119153654 |
"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a
| Author | : Christine Dugan |
| Publisher | : Triangle Interactive, Inc. |
| Total Pages | : 69 |
| Release | : 2018-03-29 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1684449634 |
Read Along or Enhanced eBook: In this inspiring and informative nonfiction title, readers will learn the ways that people start from almost nothing to become millionaires and billionaires. Through examples of hard work and smart financial decisions, readers gain an understanding of how to invest money responsibly in stocks, commodities, bonds, and mutual funds while also learning the various ways that people have been successful in entrepreneurships. Informational text, fascinating facts, and a glossary of useful terms work in conjunction with vibrant images and inspirational examples to engage readers from cover to cover.
| Author | : Jacob Yang |
| Publisher | : The Oliver Press |
| Total Pages | : 50 |
| Release | : 2019-06-12 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1545744572 |
Read Along or Enhanced eBook: Bad things can happen to people through no fault of their own?as those harmed recently by hurricanes Harvey and Irma know all too well. Whether natural or manmade, disasters have long enthralled young readers. Examining Disasters, a well-reviewed series of eight books from Clara House Books, an imprint of The Oliver Press, explores the science behind disasters. What, for example, causes airplanes to fall from the sky, or bridges to collapse, or ships to sink? For explanations, we must look to physics. It is through the study of geology that we learn how earthquakes occur. Pandemics, such as SARS or the outbreak of Ebola, affect the lives of millions. Biology, and microbiology in particular, holds the answers to how diseases are spread and how they may be prevented. Colorfully illustrated and attractively designed, Examining Disasters will grab the attention of young readers while providing the basis of scientific inquiry that the core curriculum demands.
| Author | : Anna Dalton |
| Publisher | : The Oliver Press |
| Total Pages | : 50 |
| Release | : 2019-06-12 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1545744599 |
Read Along or Enhanced eBook: Bad things can happen to people through no fault of their own?as those harmed recently by hurricanes Harvey and Irma know all too well. Whether natural or manmade, disasters have long enthralled young readers. Examining Disasters, a well-reviewed series of eight books from Clara House Books, an imprint of The Oliver Press, explores the science behind disasters. What, for example, causes airplanes to fall from the sky, or bridges to collapse, or ships to sink? For explanations, we must look to physics. It is through the study of geology that we learn how earthquakes occur. Pandemics, such as SARS or the outbreak of Ebola, affect the lives of millions. Biology, and microbiology in particular, holds the answers to how diseases are spread and how they may be prevented. Colorfully illustrated and attractively designed, Examining Disasters will grab the attention of young readers while providing the basis of scientific inquiry that the core curriculum demands.
| Author | : Philip E. Tetlock |
| Publisher | : Crown |
| Total Pages | : 331 |
| Release | : 2015-09-29 |
| Genre | : Business & Economics |
| ISBN | : 080413670X |
NEW YORK TIMES BESTSELLER • NAMED ONE OF THE BEST BOOKS OF THE YEAR BY THE ECONOMIST “The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow.”—Jason Zweig, The Wall Street Journal Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week’s meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even experts’ predictions are only slightly better than chance. However, an important and underreported conclusion of that study was that some experts do have real foresight, and Tetlock has spent the past decade trying to figure out why. What makes some people so good? And can this talent be taught? In Superforecasting, Tetlock and coauthor Dan Gardner offer a masterwork on prediction, drawing on decades of research and the results of a massive, government-funded forecasting tournament. The Good Judgment Project involves tens of thousands of ordinary people—including a Brooklyn filmmaker, a retired pipe installer, and a former ballroom dancer—who set out to forecast global events. Some of the volunteers have turned out to be astonishingly good. They’ve beaten other benchmarks, competitors, and prediction markets. They’ve even beaten the collective judgment of intelligence analysts with access to classified information. They are "superforecasters." In this groundbreaking and accessible book, Tetlock and Gardner show us how we can learn from this elite group. Weaving together stories of forecasting successes (the raid on Osama bin Laden’s compound) and failures (the Bay of Pigs) and interviews with a range of high-level decision makers, from David Petraeus to Robert Rubin, they show that good forecasting doesn’t require powerful computers or arcane methods. It involves gathering evidence from a variety of sources, thinking probabilistically, working in teams, keeping score, and being willing to admit error and change course. Superforecasting offers the first demonstrably effective way to improve our ability to predict the future—whether in business, finance, politics, international affairs, or daily life—and is destined to become a modern classic.
| Author | : Harry Knoors |
| Publisher | : Oxford University Press |
| Total Pages | : 689 |
| Release | : 2015-06-10 |
| Genre | : Psychology |
| ISBN | : 0190215208 |
Education in general, and education for deaf learners in particular, has gone through significant changes over the past three decades. And change certainly will be the buzzword in the foreseeable future. The rapid growth of information and communication technology as well as progress in educational, psychological, and allied research fields have many scholars questioning aspects of traditional school concepts. For example, should the classroom be "flipped" so that students receive instruction online at home and do "homework" in school? At the same time, inclusive education has changed the traditional landscape of special education and thus of deaf education in many if not all countries, and yet deaf children continued to lag significantly behind hearing peers in academic achievement. As a consequence of technological innovations (e.g., digital hearing aids and early bilateral cochlear implants), the needs of many deaf learners have changed considerably. Parents and professionals, however, are just now coming to recognize that there are cognitive, experiential, and social-emotional differences between deaf and hearing students likely to affect academic outcomes. Understanding such differences and determining ways in which to accommodate them through global cooperation must become a top priority in educating deaf learners. Through the participation of an international, interdisciplinary set of scholars, Educating Deaf Learners takes a broader view of learning and academic achievement than any previous work, considering the whole child. In adopting this broad perspective, the authors capture the complexities and commonalities in the social, emotional, cognitive, and linguistic mosaic of which the deaf child is a part. It is only through such a holistic consideration that we can understand their academic potential.
| Author | : Christoph Molnar |
| Publisher | : Lulu.com |
| Total Pages | : 320 |
| Release | : 2020 |
| Genre | : Artificial intelligence |
| ISBN | : 0244768528 |
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
