Author: Daniel R. Sarewitz Publisher: ISBN: Category : Education Languages : en Pages : 434
Book Description
Based upon ten case studies, Prediction explores how science-based predictions guide policy making and what this means in terms of global warming, biogenetically modifying organisms and polluting the environment with chemicals.
Author: Laurie Keller Publisher: Henry Holt and Company (BYR) ISBN: 125022599X Category : Juvenile Fiction Languages : en Pages : 23
Book Description
A potato and his eggplant nemesis struggle to find the perfect pants in this hilarious, heartwarming tale of forgiveness by bestselling Geisel-Award winning creator Laurie Keller. Potato is excited because today—for one day only— Lance Vance’s Fancy Pants Store is selling . . .POTATO PANTS! Potato rushes over early, but just as he’s about to walk in, something makes him stop. What could it be? Find out in this one-of-a-kind story about misunderstandings and forgiveness, and—of course—Potato Pants! A Christy Ottaviano Book This title has Common Core connections.
Author: Nicolo Cesa-Bianchi Publisher: Cambridge University Press ISBN: 113945482X Category : Computers Languages : en Pages : 4
Book Description
This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual sequences does not impose any probabilistic assumption on the data-generating mechanism. Yet, prediction algorithms can be constructed that work well for all possible sequences, in the sense that their performance is always nearly as good as the best forecasting strategy in a given reference class. The central theme is the model of prediction using expert advice, a general framework within which many related problems can be cast and discussed. Repeated game playing, adaptive data compression, sequential investment in the stock market, sequential pattern analysis, and several other problems are viewed as instances of the experts' framework and analyzed from a common nonstochastic standpoint that often reveals new and intriguing connections.
Author: Edward R. Dewey Publisher: Simon and Schuster ISBN: 1681462737 Category : Business & Economics Languages : en Pages : 304
Book Description
It is the business of science to predict. An exact science like astronomy can usually make very accurate predictions indeed. A chemist makes a precise prediction every time he writes a formula. The nuclear physicist advertised to the world, in the atomic bomb, how man can deal with entities so small that they are completely beyond the realm of sense perception, yet make predictions astonishing in their accuracy and significance. Economics is now reaching a point where it can hope also to make rather accurate predictions, within limits which this study will explain. This is the only eBook edition that comes complete with more than 150 graphs and charts.
Author: David Shannon Publisher: Scholastic Inc. ISBN: 0545530032 Category : Juvenile Fiction Languages : en Pages : 42
Book Description
In this off-beat book perfect for reading aloud, a Caldecott Honor winner shares the story of a duck who rides a bike with hilarious results. One day down on the farm, Duck got a wild idea. “I bet I could ride a bike,” he thought. He waddled over to where the boy parked his bike, climbed on, and began to ride. At first, he rode slowly and he wobbled a lot, but it was fun! Duck rode past Cow and waved to her. “Hello, Cow!” said Duck. “Moo,” said Cow. But what she thought was, “A duck on a bike? That’s the silliest thing I’ve ever seen!” And so, Duck rides past Sheep, Horse, and all the other barnyard animals. Suddenly, a group of kids ride by on their bikes and run into the farmhouse, leaving the bikes outside. Now ALL the animals can ride bikes, just like Duck! Praise for Duck on a Bike “Shannon serves up a sunny blend of humor and action in this delightful tale of a Duck who spies a red bicycle one day and gets “a wild idea” . . . Add to all this the abundant opportunity for youngsters to chime in with barnyard responses (“M-o-o-o”; “Cluck! Cluck!”), and the result is one swell read-aloud, packed with freewheeling fun.” —Publishers Weekly “Grab your funny bone—Shannon . . . rides again! . . . A “quackerjack” of a terrific escapade.” —Kirkus Reviews
Author: Andreas S. Weigend Publisher: Routledge ISBN: 042997227X Category : Social Science Languages : en Pages : 665
Book Description
The book is a summary of a time series forecasting competition that was held a number of years ago. It aims to provide a snapshot of the range of new techniques that are used to study time series, both as a reference for experts and as a guide for novices.
Author: Maxime C. Cohen Publisher: Springer Nature ISBN: 3030858553 Category : Business & Economics Languages : en Pages : 166
Book Description
From data collection to evaluation and visualization of prediction results, this book provides a comprehensive overview of the process of predicting demand for retailers. Each step is illustrated with the relevant code and implementation details to demystify how historical data can be leveraged to predict future demand. The tools and methods presented can be applied to most retail settings, both online and brick-and-mortar, such as fashion, electronics, groceries, and furniture. This book is intended to help students in business analytics and data scientists better master how to leverage data for predicting demand in retail applications. It can also be used as a guide for supply chain practitioners who are interested in predicting demand. It enables readers to understand how to leverage data to predict future demand, how to clean and pre-process the data to make it suitable for predictive analytics, what the common caveats are in terms of implementation and how to assess prediction accuracy.
Author: Ray C. Fair Publisher: Stanford University Press ISBN: 9780804745093 Category : Political Science Languages : en Pages : 196
Book Description
What do the following events have in common? In 2000, the election between George W. Bush and Al Gore was a virtual tie. The 1989 and 1990 vintages have turned out to be two of the best ever for Bordeaux wines. In 2001, the Federal Reserve lowered the interest rate eleven times. The decade of the 1970s was one of the worst on record for U.S. inflation. In 2001, the author of this book, at age 59, ran a marathon in 3 hours and 30 minutes, but should have been able to do it in 3 hours and 15 minutes. This book shows clearly and simply how these diverse events can be explained by using the tools of the social sciences and statistics. It moves from a discussion of formulating theories about real world phenomena to lessons on how to analyze data, test theories, and make predictions. Through the use of a rich array of examples, the book demonstrates the power and range of social science and statistical methods. In addition to “big” topics—presidential elections, Federal Reserve behavior, and inflation—and “not quite so big” topics—wine quality—the book takes on questions of more direct, personal interest. Who of your friends is most likely to have an extramarital affair? How important is class attendance for academic performance in college? How fast can you expect to run a race or perform some physical task at age 55, given your time at age 30? (In other words, how fast are you slowing down?) As the author works his way through an incredibly broad range of questions and topics, demonstrating the usefulness of statistical theory and method, he gives the reader a new way of thinking about many age-old concerns in public and private life.
Author: David Nabhan Publisher: Simon and Schuster ISBN: 1510720987 Category : Science Languages : en Pages : 240
Book Description
Each year the world faces thousands of earthquakes of magnitude 5.0 or greater, resulting in devastating property destruction and tragic loss of life. To help avert these catastrophes, scientists have long searched for ways to predict when and where earthquakes will happen. The earth science establishment in the US says that earthquake prediction still lies outside the realm of possibility. But recent scientific developments across the globe suggest that seismic forecasting is on the horizon. Earthquake Prediction: Dawn of the New Seismology examines the latest scientific clues in hopes of discovering seismic precursors which may shed light on real earthquake prediction in the future. It is destined to be nothing less than an epoch-changing work, addressing this ancient enigma by joining the parts of a scientific detective story that ranges from the steppes of Russia to the coast of Chile, bringing to light astounding breakthroughs by researchers in Italy, India and elsewhere. Governments in countries such as China and Japan provide support for seismic forecasting, and it is time for our country to do the same. Earthquake Prediction makes the case, with an important message for the tens of millions of Americans on the US West Coast, the Mississippi River Valley, and other seismically active zones.
Author: Vineeth Balasubramanian Publisher: Newnes ISBN: 0124017150 Category : Computers Languages : en Pages : 323
Book Description
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detection. As practitioners and researchers around the world apply and adapt the framework, this edited volume brings together these bodies of work, providing a springboard for further research as well as a handbook for application in real-world problems. - Understand the theoretical foundations of this important framework that can provide a reliable measure of confidence with predictions in machine learning - Be able to apply this framework to real-world problems in different machine learning settings, including classification, regression, and clustering - Learn effective ways of adapting the framework to newer problem settings, such as active learning, model selection, or change detection
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Author: Daniel R. Sarewitz
Author: Laurie Keller
Author: Nicolo Cesa-Bianchi
Author: Edward R. Dewey
Author: David Shannon
Author: Andreas S. Weigend
Author: Maxime C. Cohen
Author: Ray C. Fair
Author: David Nabhan
Author: Vineeth Balasubramanian