Book picks similar to
Abstract Algebra by I.N. Herstein
mathematics
math
algebra
maths
The De-Textbook: The Stuff You Didn't Know About the Stuff You Thought You Knew
Cracked.com - 2013
For decades your teachers, authority figures and textbooks have been lying to you. You do not have five senses. Your tongue doesn't have neatly segregated taste-bud zones. You don't know what the pyramids really looked like. You're even pooping wrong - Jesus, you're a wreck!But it's going to be okay. Because we're here to help. Packed with more sexy facts than the Encyclopedia Pornographica, the Cracked De-Textbook will teach you about the true stars of history, why you picture everything from Velociraptors to Ancient Rome incorrectly, and finally, at long last - how to pop a proper squat. This book was built from the ground up to systematically seek out, dismantle and destroy the many untruths that years of misguided education have left festering inside of you, and leave you a smarter person...whether you like it or not. The De-Textbook is a merciless, brutal learning machine. It can't be bargained with. It can't be reasoned with. It doesn't feel pity, or remorse, or fear. And it absolutely will not stop, ever, until you are informed.
Statistics Done Wrong: The Woefully Complete Guide
Alex Reinhart - 2013
Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong."Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.In this book, you'll learn: - Why "statistically significant" doesn't necessarily imply practical significance- Ideas behind hypothesis testing and regression analysis, and common misinterpretations of those ideas- How and how not to ask questions, design experiments, and work with data- Why many studies have too little data to detect what they're looking for-and, surprisingly, why this means published results are often overestimates- Why false positives are much more common than "significant at the 5% level" would suggestBy walking through colorful examples of statistics gone awry, the book offers approachable lessons on proper methodology, and each chapter ends with pro tips for practicing scientists and statisticians. No matter what your level of experience, "Statistics Done Wrong" will teach you how to be a better analyst, data scientist, or researcher.
Data Mining: Practical Machine Learning Tools and Techniques
Ian H. Witten - 1999
This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915 0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today's Computers
John MacCormick - 2012
A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more. These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.
Options, Futures and Other Derivatives
John C. Hull
Changes in the fifth edition include: A new chapter on credit derivatives (Chapter 21). New! Business Snapshots highlight real-world situations and relevant issues. The first six chapters have been -reorganized to better meet the needs of students and .instructors. A new release of the Excel-based software, DerivaGem, is included with each text. A useful Solutions Manual/Study Guide, which includes the worked-out answers to the "Questions and Problems" sections of each chapter, can be purchased separately (ISBN: 0-13-144570-7).