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Minggu, 17 Juni 2012

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Kamis, 14 Juni 2012

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Minggu, 10 Juni 2012

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Rabu, 06 Juni 2012

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There are many great books that teach data and machine-learning skills. Those books are similar to books on programming languages; they teach valuable skills in great detail. This book is more like a book on software engineering; it teaches how to take those base skills and produce working systems. This book is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. I hope this book helps accelerate the proliferation of systems that turn data into impact and helps readers develop practical skills in this important area. Who This Book Is For This book is for anyone with a computer science degree who wants to understand what it takes to build effective Intelligent Systems. Imagine a typical software engineer who is assigned to a machine learning project. 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For example, you may not be getting all the training data you'd like because of telemetry sampling. Should you double down on modeling around the problem, or would an engineering solution make more sense? Or maybe you are being pushed to optimize for a difficult extremely-high precision, when your models are already performing at a very good (but slightly lower) precision. Should you keep chasing that super-high precision or should you work to influence the user experience in ways that reduce the customer impact of mistakes? Third, it's important to understand how the supporting systems can benefit you.The escalation paths, the manual over-rides, the telemetry, the guardrails that prevent against major mistakes--these are all tools you can leverage. You need to understand when to use them and how to integrate them with your modeling process. Should you discard a model that works acceptably for 99% of users but really, really badly for 1% of users? Or maybe you can count on other parts of the system to address the problem. Software Engineers Building software that delights customers is a lot of work. No way around it, behind every successful software product and service there is some serious engineering. Intelligent Systems have some unique properties which present interesting challenges. This book describes the associated concepts so you can design and build Intelligent Systems that are efficient, reliable, and that best-unlock the power of machine learning and data science. First, this book will identify the entities and abstractions that need to exist within a successful Intelligent System. You will learn the concepts behind the intelligence run time, context and features, models, telemetry,training data, intelligence management, orchestration, and more. Second, the book will give you a conceptual understanding of machine learning and data sciences. 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The first thing you'll learn is to develop an intuition for when machine learning and data science are appropriate. There is nothing worse than trying to hammer a square peg into a round hole. You need to understand what types of problems can be solved by machine learning. But just as importantly,you need to understand what types of problems can't be--or at least not easily.There are so many participants in a successful endeavor, and they speak such different, highly-technical, languages, that this is particularly difficult.This book will help you understand enough so you can ask the right questions and understand what you need from the answers. The second is to get an intuition on return on investment so you can determine how much Intelligent System to use. By understanding the real costs of building and maintaining a system that turns data into impact you can make better choices about when to do it. You can also go into it with open eyes, and have the investment level scoped for success. Sometimes you need all the elements described in this book, but sometimes the right choice for your business is something simpler. This book will help you make good decisions and communicate them with confidence and credibility. Read morePaperback=339 pages. Publisher=Apress; 1st ed. edition (March 7, 2018). Language=English. ISBN-10=1484234316. ISBN-13=978-1484234310. Product Dimensions=7 x 0.8 x 10 inches. Shipping Weight=1.4 pounds (View shipping rates and policies). Average Customer Review=5.0 out of 5 stars 14 customer reviews. Amazon Best Sellers RankData ProcessingComputer ScienceComputer Science=#64,684 in Books (See Top 100 in Books) .zg_hrsr { margin: 0; padding: 0; list-style-type: none; } .zg_hrsr_item { margin: 0 0 0 10px; } .zg_hrsr_rank { display: inline-block; width: 80px; text-align: right; } #55 in Books > Computers & Technology > Databases & Big Data > #416 in Books > Computers & Technology > #833 in Books > Textbooks >.

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Minggu, 03 Juni 2012

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Sabtu, 02 Juni 2012

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Review "Rich in humor, acutely observant, Dahl lets his imagination rip in fairyland." —The New York Times Read more About the Author Roald Dahl was a spy, ace fighter-pilot, chocolate historian and medical inventor. He was also the author of Charlie and the Chocolate Factory, Matilda, The BFG and many more brilliant stories. He remains the World’s No.1 storyteller. Find out more at roalddahl.com. Read moreAge Range=8 - 12 years. Grade Level=3 - 7. Lexile Measure=810L (What's this?). Paperback=192 pages. Publisher=Puffin Books; Reprint edition (August 16, 2007). Language=English. ISBN-10=0142410314. ISBN-13=978-0142410318. Product Dimensions=5.1 x 0.5 x 7.8 inches. Shipping Weight=6.4 ounces (View shipping rates and policies). Average Customer Review=4.7 out of 5 stars 1,272 customer reviews. Amazon Best Sellers RankClassicsFantasy & MagicAction & Adventure=#1,153 in Books (See Top 100 in Books) .zg_hrsr { margin: 0; padding: 0; list-style-type: none; } .zg_hrsr_item { margin: 0 0 0 10px; } .zg_hrsr_rank { display: inline-block; width: 80px; text-align: right; } #47 in Books > Children's Books > #55 in Books > Children's Books > Science Fiction & Fantasy > #65 in Books > Children's Books >.

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