Minggu, 26 Oktober 2014

[M668.Ebook] Download PDF Empire Lite: Nation-Building in Bosnia, Kosovo, and Afghanistan, by Michael Ignatieff

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Empire Lite: Nation-Building in Bosnia, Kosovo, and Afghanistan, by Michael Ignatieff

  • Sales Rank: #1726470 in Books
  • Published on: 2003
  • Number of items: 1
  • Dimensions: 8.50" h x .34" w x 5.50" l,
  • Binding: Paperback
  • 134 pages

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Senin, 20 Oktober 2014

[T939.Ebook] Free Ebook Inborn Metabolic Diseases: Diagnosis and TreatmentFrom Springer

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Inborn Metabolic Diseases: Diagnosis and TreatmentFrom Springer

This work is recognised as the standard textbook for professionals involved in the diagnosis and management of inborn errors of metabolism (IEM) and an essential resource in this multidisciplinary field. For the 6th edition all 43 chapters have been newly written or revised by authors with particular expertise in their subject areas.

Contents: A clinical and biochemical approach to the recognition and diagnosis of IEM with algorithms to symptoms, signs, and syndromes in patients of all ages; Emergency treatments; Medications – Separate comprehensive sections on IEM of: Carbohydrates; Mitochondrial Energy; Amino and organic acids; Vitamin-responsive defects; Neurotransmitter and Small peptides, Lipid and Bile Acids; Nucleic Acid and Heme; Organelles –�Disorders affecting the synthesis and remodelling of complex lipids and fatty acid homeostasis are now included.�

  • Sales Rank: #1719960 in Books
  • Published on: 2016-12-21
  • Original language: English
  • Number of items: 1
  • Dimensions: 10.20" h x .0" w x 7.60" l, .0 pounds
  • Binding: Hardcover

From the Back Cover

This work is recognised as the standard textbook for professionals involved in the diagnosis and management of inborn errors of metabolism (IEM) and an essential resource in this multidisciplinary field. For the 6th edition all 43 chapters have been newly written or revised by authors with particular expertise in their subject areas.

Contents

A clinical and biochemical approach to the recognition and diagnosis of IEM with algorithms to symptoms, signs, and syndromes in patients of all ages; Emergency treatments; Medications.

Separate comprehensive sections on IEM of: Carbohydrates; Mitochondrial Energy; Amino and organic acids; Vitamin-responsive defects; Neurotransmitter and Small peptides, Lipid and Bile Acids; Nucleic Acid and Heme; Organelles.

Disorders affecting the synthesis and remodelling of complex lipids and fatty acid homeostasis are now included.

The Editors

Jean-Marie Saudubray, M.D., is Emeritus Professor of Pediatrics and Expert Metabolic Consultant at the adult neuro-metabolic unit in the H�pital La Piti� Salp�tri�re from the Universit� Pierre et Marie Curie, Paris.

Matthias R. Baumgartner, M.D., Professor of Paediatrics and Inherited Metabolic Medicine, University of Zurich, is Head of the Division of Metabolism and the Swiss Newborn Screening Programme at the University Children’s Hospital, Zurich.

John Walter, M.D. is Honorary Clinical Professor of Inherited Metabolic Medicine, Manchester Academic Health Science Centre, Willink Unit, Manchester.

About the Author

Jean-Marie Saudubray, M.D., is Emeritus Professor of Pediatrics and Expert Metabolic Consultant at the adult neuro-metabolic unit in the H�pital La Piti� Salp�tri�re from the Universit� Pierre et Marie Curie, Paris.

Matthias R. Baumgartner, M.D., Professor of Paediatrics and Inherited Metabolic Medicine, University of Zurich, is Head of the Division of Metabolism and the Swiss Newborn Screening Programme at the University Children’s Hospital, Zurich.

John Walter, M.D. is Honorary Clinical Professor of Inherited Metabolic Medicine, Manchester Academic Health Science Centre, Willink Unit, Manchester.

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Jumat, 17 Oktober 2014

[G658.Ebook] Free Ebook Machine Learning with R, by Brett Lantz

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Machine Learning with R, by Brett Lantz

R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required - this book will take you methodically through every stage of applying machine learning.

Overview

  • Harness the power of R for statistical computing and data science
  • Use R to apply common machine learning algorithms with real-world applications
  • Prepare, examine, and visualize data for analysis
  • Understand how to choose between machine learning models
  • Packed with clear instructions to explore, forecast, and classify data

In Detail

Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning. Whether you are new to data science or a veteran, machine learning with R offers a powerful set of methods for quickly and easily gaining insight from your data.

"Machine Learning with R" is a practical tutorial that uses hands-on examples to step through real-world application of machine learning. Without shying away from the technical details, we will explore Machine Learning with R using clear and practical examples. Well-suited to machine learning beginners or those with experience. Explore R to find the answer to all of your questions.

How can we use machine learning to transform data into action? Using practical examples, we will explore how to prepare data for analysis, choose a machine learning method, and measure the success of the process.

We will learn how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.

"Machine Learning with R" will provide you with the analytical tools you need to quickly gain insight from complex data.

What you will learn from this book

  • Understand the basic terminology of machine learning and how to differentiate among various machine learning approaches
  • Use R to prepare data for machine learning
  • Explore and visualize data with R
  • Classify data using nearest neighbor methods
  • Learn about Bayesian methods for classifying data
  • Predict values using decision trees, rules, and support vector machines
  • Forecast numeric values using linear regression
  • Model data using neural networks
  • Find patterns in data using association rules for market basket analysis
  • Group data into clusters for segmentation
  • Evaluate and improve the performance of machine learning models
  • Learn specialized machine learning techniques for text mining, social network data, and “big” data

Approach

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.

  • Sales Rank: #453633 in Books
  • Published on: 2013-10-25
  • Released on: 2013-10-25
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.25" h x .90" w x 7.50" l, 1.49 pounds
  • Binding: Paperback
  • 396 pages

About the Author

Brett Lantz

Brett Lantz has spent the past 10 years using innovative data methods to understand human behavior. A sociologist by training, he was first enchanted by machine learning while studying a large database of teenagers' social networking website profiles. Since then, he has worked on interdisciplinary studies of cellular telephone calls, medical billing data, and philanthropic activity, among others. When he's not spending time with family, following college sports, or being entertained by his dachshunds, he maintains dataspelunking.com, a website dedicated to sharing knowledge about the search for insight in data.

Most helpful customer reviews

33 of 34 people found the following review helpful.
There are some useful gems in this book
By Philip H.
I'm torn. There are some useful gems in this book, and for the most part, the presentation is simple, albeit a bit pedantic and cartoonish at times. If I was trying to get up to snuff on a new machine learning method, I might start here, since it *does* provide starter code for a variety of problems. That's quite handy. It doesn't, however, go into much depth at all on any one topic. You can't read this book and expect to know how to do any one of these methods well. Certainly, it's a tall order to ask any one book to cover all ML topics in depth, but any potential reader should be aware that this just skims the surface of a whole bunch of topics.

On top of this, who in the world edited this book? Every other page has horrible typos, missing words, repeated sentences. These are not trivial errors either. This is a book about data analysis and yet the reported data are clearly wrong in places, e.g., a result is listed as .06 percent in one spot and then .0006 in another (p. 271). Basic subject-verb agreement errors riddle the text, e.g. "These output is shown as follows". Sometimes these are trivial errors, but other times you have absolutely no idea what the intended meaning is. I have about 100 pages more to read but I'm starting to wonder if I'm just wasting my time.

43 of 45 people found the following review helpful.
Less tech speak, more meaty
By Amazon Customer
First off, I am newbie to both machine learning and R and wanted find a starting point somewhere. I browsed around many books before deciding on this one. The writing style of Mr. Lantz is provided in a very understandable/readable manner. It's akin to someone sitting next to you and explaining things in a down to earth, layman's fashion rather than try to "tech speak" you to death with complicated explanations (aka formal textbook). Just the right amount of hand holding for me. I highlight quite bit and it's actually difficult with this book as there isn't much fluff. He's very succinct. The books states that it's for someone who know some ML and no R or R and no ML. I don't know either and the material is digestible except for one thing: review your stats! I took statistics long ago in college and never really learned it well the first time so I had stop and reread core concepts before continuing. Do yourself a favor and review basic statistics and probability before you start this book. I read both "Naked Statistics" and "Statistics in Plain English" and it helped me a great deal (and probably will continue to do so since it appears a bulk of machine learning is stats and prob). Currently into about a third of the way in and I am finding it to be very enjoyable and practical. Other reviewers point out that this book is too basic and this may be the case, but for someone like me who is starting from absolute scratch and who needs to understand basic ML concepts (AND basic R) I find it a great book. Will post an addendum once I complete it.

5 of 5 people found the following review helpful.
Best ML learning resource I've found
By Dim Dandy
This book is fantastic. I've been through the first four chapters, so I can't give a complete review yet, but if the rest of the book conains surprises, I will update.

Chapter 3 is on k-nearest neighbor and chapter 4 is on naive Bayes. Both provide a clear explanation of the technique, and its pros and cons, along with a simple, non-programming example. Then there is an excellent walkthrough of applying the technique to real world data, and some hints at how to improve the results by adjusting the inputs. After each chapter, I felt that I was ready to apply the technique, with the understanding that I did not yet understand everything about the topic. The chapters also are careful to explain that 1) the particular R package used has more options than have been covered and 2) there are other R packages to be investigated and experimented with.

I just couldn't be happier with these chapters, and I am fired up to keep reading and working along with the examples. It has been years since I have been reading a tech book and thinking, "OK, just a little bit more, I don't want to quit yet" instead of, "Have I spent enough time and effort on this for one day yet?" It's that good.

Although the book does provide a bit of an introduction to R, it is by no means comprehensive, and I have found that R takes time, patience and frustration to master (not that I've mastered it yet). So if I had been a complete R newbie, I probably would have struggled more.

I also found that a recent course I took in statistical inference was helpful, although not really required. At one point the book describes normalizing features using Z scores. I knew what Z scores were, so that was a point I didn't need to simply take on faith.

If you are relatively new to R and machine learning, and you want to learn to do machine learning with R, this *is* the book.

UPDATE: I am working through chapter 10, on validating model performance, and it is a goldmine. Maybe it's a matter of my general knowledge about machine learning concepts coalescing at the same time I'm reading this chapter, but it was like a long line of lightbulbs were getting switched on in my head.

UPDATE 2: I've now read the entire book and chapter 11, on improving model performance, was invaluable. It introduces random forests, and somehow finds a way to make the concept easy to comprehend, where every other article I've read or video I've watched made it seem very complicated. This chapter has given me the confidence to start tackling more sophisticated kaggle competitions using ensemble methods. Really looking forward to it.

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Rabu, 15 Oktober 2014

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  • Sales Rank: #1825389 in Books
  • Binding: Hardcover

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Selasa, 07 Oktober 2014

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[ Semiconductor Sensors , by Sze, S M ( Author ) Hardcover 1994 ], by S M Sze

  • Published on: 1994
  • Binding: Hardcover

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Minggu, 05 Oktober 2014

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Destined for War: Can America and China Escape Thucydides’s Trap?, by Graham Allison

CHINA AND THE UNITED STATES ARE HEADING TOWARD A WAR NEITHER WANTS. The reason is Thucydides’s Trap, a deadly pattern of structural stress that results when a rising power challenges a ruling one. This phenomenon is as old as history itself. About the Peloponnesian War that devastated ancient Greece, the historian Thucydides explained: “It was the rise of Athens and the fear that this instilled in Sparta that made war inevitable.” Over the past 500 years, these conditions have occurred sixteen times. War broke out in twelve of them. Today, as an unstoppable China approaches an immovable America and both Xi Jinping and Donald Trump promise to make their countries “great again,” the seventeenth case looks grim. Unless China is willing to scale back its ambitions or Washington can accept becoming number two in the Pacific, a trade conflict, cyberattack, or accident at sea could soon escalate into all-out war.

In Destined for War, the eminent Harvard scholar Graham Allison explains why Thucydides’s Trap is the best lens for understanding U.S.-China relations in the twenty-first century. Through uncanny historical parallels and war scenarios, he shows how close we are to the unthinkable. Yet, stressing that war is not inevitable, Allison also reveals how clashing powers have kept the peace in the past — and what painful steps the United States and China must take to avoid disaster today.

  • Sales Rank: #9279 in Books
  • Published on: 2017-05-30
  • Released on: 2017-05-30
  • Original language: English
  • Dimensions: 9.00" h x 1.23" w x 6.00" l,
  • Binding: Hardcover
  • 384 pages

Review
“Thucydides’s Trap identifies a cardinal challenge to world order: the impact of a rising power on a ruling power. I read the book with great interest. I can only hope that the US-China relationship becomes the fifth case to resolve itself peacefully, rather than the 13th to result in war.” — HENRY KISSINGER, former United States Secretary of State

“Graham Allison is one of the keenest observers of international affairs around. �He consistently brings his deep understanding of history’s currents to today’s most difficult challenges and makes our toughest foreign policy dilemmas accessible to experts and everyday citizens alike. That’s why I regularly sought his counsel both as a senator and as vice president. �In Destined for War, Allison lays out one of the defining challenges of our time—managing the critical relationship between China and the United States.” — JOE BIDEN, former Vice President of the United States

“One of the most insightful and thought-provoking books I have ever read on the most important relationship in the world: the US and China. If Graham Allison is right—and I think he is—China and the US must heed the lessons in this superb study in order to build a strategic relationship that avoids a war which neither side would win.” — General (Ret.) DAVID PETRAEUS, Chairman of the KKR Global Institute, former Director of the CIA, and former Commander of US Central Command

“Can the US avoid confrontation with China? That is the geopolitical question of our age. In most cases, Thucydides was right: when a new power arises in the world, it results in a clash with the dominant power. This important and fascinating book extracts lessons for how we can avoid such a confrontation.”—WALTER ISAACSON, author of Steve Jobs and The Innovators

"A hugely respected theorist and practitioner in the field of contemporary national security, Graham Allison is also a master of applied history. You can bet that China's leaders will read Allison's warnings about Thucydides's Trap. I only wish I could be as sure about America's leaders. But every informed citizen should buy a copy." —NIALL FERGUSON,�senior fellow, the Hoover Institution, Stanford University, and author of The War of the World

"A provocative thesis on one of today's most pressing foreign policy issues and a page turner of the first order, Destined For War is a must read. �Professor Allison writes with the propulsive narrative drive appropriate for such an immediate and danger fraught topic. �I can only hope that all senior policy experts read this timely book to prevent our country from falling into the trap Professor Allison so ably warns us against." — CHRISTOPHER REICH, bestselling author of Invasion of Privacy, The Patriots’ Club, and Numbered Account

“Do China and America want war? No. Might they be compelled into conflict by severe structural stress? Yes. Thankfully, Allison charts an essential course to avoid a catastrophic collision. Destined for War will be studied and debated for decades.” — KEVIN RUDD, former Prime Minister of Australia

“In Destined for War, Graham Allison has again done a great service. With an incisive review of the wars of yesterday and a deep understanding of today’s international politics, Allison has provided American and Chinese leaders not just with a stark warning about the consequences of falling into the Thucydides’s Trap, but also the insight to avoid it.� For policymakers, scholars, and citizens on both sides of the Pacific Ocean, Destined for War is essential reading.”� — ASH CARTER, former U.S. Secretary of Defense

"Graham Allison is the Paul Revere of the nuclear age. He has been ringing the alarm for years trying to stir us from our slumber. In his brilliant book, Allison provides us with a heart stopping look into a future that may end as abruptly as the past began."� — WILLIAM COHEN, former U.S. Secretary of Defense

“In dissecting—and suggesting ways to bend—the dangerous arc of the US-China relationship, Graham Allison has written the most important foreign policy book of our time. This book should immediately be read by our new president. Placing Destined for War atop every government organization’s reading list offers our generation of leaders the best hope for avoiding stumbling into Thucydides’s notorious trap.” — ADMIRAL (RET.) SANDY WINNEFELD, former Vice Chairman of the Joint Chiefs of Staff

“Drawing on a sweeping command of history and a keen ability to distill the essence of an argument, Graham Allison has provided the necessary guide for how to manage Sino-American relations into an uncertain future. Essential, even indispensable reading for every diplomat—and financier or businessman—that contemplates China and its relations with the world.” — KURT CAMPBELL, CEO of The Asia Group and former U.S. Assistant Secretary of State for East Asian and Pacific Affairs

“Destined for War is a must-read for anyone concerned about US-China relations, or peace. And by all who care about the ways US foreign policy is formed—and ought to be formed. A gifted combination of scholarship with truly accessible writing.”—�� AMITAI ETZIONI, professor of International Affairs at The George Washington University and author of Avoiding War with China

“Reading Destined for War and drawing from its lessons could help to save the lives of millions of people.” — KLAUS SCHWAB, Founder and Executive Chairman of the World Economic Forum

“Steeped in history and propelled by one of the most transformative developments in modern times—the rise of China—Graham Allison has written a gripping book that decision-makers and citizens alike must read, digest, and act upon. Allison combines a historian’s depth of knowledge with a policymaker’s real world, practical understanding. He mines the recent and distant past to offer essential insights into the future — in so doing, changing the way we think about how America should act in the present.” — SAMANTHA POWER, former US Ambassador to the United Nations and Pulitzer Prize-winning author of A Problem from Hell

“If any book can stop a world war, it is this one. Graham Allison makes a clear and compelling case that serious conflict between the United States and China is looming, but not inevitable.� This gripping book is a must read for policy makers in both nations as well as the general public.” — SAM NUNN, Co-Chairman of the Nuclear Threat Initiative and former US Senator (1972-1996)

About the Author
GRAHAM ALLISON is director of Harvard Kennedy School's Belfer Center for Science and International Affairs and the best-selling author of LeeKuan Yew: The Grand Master's Insights on China, the United States, and the World; Nuclear Terrorism: The Ultimate Preventable Catastrophe; and Essence of Decision: Explaining the Cuban Missile Crisis. Founding dean of the Harvard Kennedy School, Dr. Allison has served as Assistant Secretary of Defense and advised the secretaries of defense under every president from Reagan to Obama. He lives in Belmont, Massachusetts.

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