Kamis, 30 Agustus 2012

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The Last Punisher: A SEAL Team Three Sniper's True Account of the Battle of Ramadi, by Kevin Lacz, Ethan E. Rocke, Lincy Lacz

The Last Punisher is a bold, no-holds-barred first-person account of the Iraq War. With wry humor and moving testimony, Kevin Lacz tells the story of his tour in Iraq with SEAL Team Three, the warrior elite of the navy. This legendary unit, known as The Punishers, included Chris Kyle (American Sniper), Mike Monsoor, Ryan Job, and Marc Lee. These brave men were instrumental in securing the key locations in the pivotal 2006 Battle of Ramadi, told with stunning detail in this book.

Minute by minute, Lacz relays the edge-of-your-seat details of his team's missions in Ramadi, offering a firsthand glimpse into the heated combat, extreme conditions, and harrowing experiences they faced every day. Through it all, Lacz and his teammates formed unbreakable bonds and never lost sight of the cause: protecting America with their fight.

The Last Punisher brings the listener into the life and mind of a SEAL, demonstrating the tough realities of war. At the same time, Lacz shares how these experiences made him a better man and how proud he is of his contributions to one of this country's most difficult military campaigns.

  • Sales Rank: #1846 in Audible
  • Published on: 2016-08-16
  • Released on: 2016-08-16
  • Format: Unabridged
  • Original language: English
  • Running time: 537 minutes

Most helpful customer reviews

63 of 67 people found the following review helpful.
Thank God He Gave Us SEAL Team Warriors
By Chuck Roast
FULL DISCLOSURE: I have friends who are former Teams guys who, along the way, helped me stay safe in my career thus I do have a special place in my heart for these guys. That said, I've never met Mr. Lacz so I have no personal connection with him though I learned, after reading his book that he apparently lives in my old stomping grounds in the Panhandle.

I bought this book after seeing him on Fox & Friends talking about his book. I decided I'd buy it as a way of quietly supporting him and those who have fought for us. I figured it would be like all the other books out there where authors talks more about their accomplishment, with perhaps some embellishments here and there, mix in a little CDI (chick dig it) lingo and presto "I'm a hero." That is NOT the case at all here. Mr. Lacz gives the ground truth of war and the warriors who fight to protect our freedoms along with his own experiences, warts and all.

The Last Punisher will put you under the helmet and in the books kicking of moon dust as you walk the streets of Ramadi. But where other "warrior" books want to share only the "good" stuff, Lacz shares some of the otherwise "boring" stuff to give the reader a better perspective of how things actually happen. He talks about the number of times they got geared up, stressed trying to get to their objective, finding nothing, then stressed getting safely back home. It happens. Not every day is profitable. Yet they still paid the fee in sweat equity and fatigue only to come up empty handed. But when they were profitable, grab your backside and hold on. If you've seen the movies; American Sniper, Lone Survivor, 13 hrs, and so forth, you can easily visualize where Lacz is taking you. You can easily visualize how SEALs move from cover to cover. You walk along side of him, preparing for a direct action contact. And you're there with the guys witnessing him screwing things up.

But beyond putting you under the helmet, Lacz puts you in the head of a warrior and shares what it take to survive mentally. And why, when they come back home, they have nowhere near the difficulty readjusting to life than the other 98% of us would have. Sure their humor may be "sick" to some. Sure they may find something funny it's hitting the fan. It is something very difficult to grasp if you've never been there and Lacz takes us to there. "Teams and shhhstuff." (Forgive me Dauber but Amazon censors)

Lacz does not get into the politics of war save for the REMFs (get the book for the definition) who were calling the shots putting people in harms way oftentimes with poor judgment. The politics were clearly pay grades above his and I believe he was right to leave his opinions out of this book. For managers and supervisor, pay attention here. Learn to read your people. Learn how to feed them and how to rest them. Learn how to keep them hungry for more. And if you're not shedding tears when he shares bringing Marc Lee (HOOYAH! MARC LEE) home, you're not human and you need to get yourself checked out.

If you're an American, if you love this country, please show your support with the purchase of this book. It's such a small price to pay for what he and the SEAL Team THREE "Punishers" have given you.

5 of 5 people found the following review helpful.
Like most good SEAL books
By Mark L.
BTF and buy this book

I give "The Last Punisher" 5 stars because it not only exceeded my expectations but it made an effect on my own life. I was anticipating a "cool" SEAL book but what I read was a very well written book about a young man who I have a lot in common with. The author gives a realistic, in depth description of the gnarliest ground battle in the Iraq war. Like most good SEAL books, "The Last Punisher" is filled with intense action and cool weapons. What separates this book is that it reads more like a novel, developing characters, personifying war and the juxtaposition of life and death. Throughout the book I found myself laughing, crying, understanding and learning about how 1% of people are capable of such things as becoming a US Navy SEAL, being able to confront the enemy downrange and send a heavy dose of US ammunition while serving as a steward of the flag.

I personally was inspired to change my life and find my own inner SEAL throughout my own life. The motivating mantra to "BTF" (big tough frog) right through tough points in your life is a message that everyone can relate to. In the business world, I work with a team of individuals who need to work together to accomplish their goals. The way Kevin describes his training, preparation, communication and the execution of his teams missions gave me a new insight on how I could do the same with mine.

I would recommend this book to anyone who is looking for fascinating account of a true American hero. You will not want to put this book down and when you are finished, you'll want to BTF your life.

8 of 8 people found the following review helpful.
awesome book
By reader247
Best book on the teams I've read. Fast furious funny. I think this book speaks to the heart of war like few do. Great in every sense.

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Rabu, 29 Agustus 2012

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  • Sales Rank: #9367624 in Books
  • Original language: French
  • Dimensions: 5.51" h x .47" w x 7.87" l,
  • Binding: Paperback

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Rabu, 22 Agustus 2012

[V174.Ebook] Ebook Free Comprehensive lipid testing and management, by Lars Carlson

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Cardiovascular disease is a major cause of morbidity and mortality in developed countries. Measurement of blood of lipids and lipoproteins has become one of the most frequently performed assays in clinical chemistry laboratories, reflecting their role in the aetiology of cardiovascular disease.
Pocket Reference to Comprehensive Lipid Testing and Management provides an overview of the purpose of lipid testing, diagnosis and lipid profiles as well as the goals of treatment and pharmacological management of lipid levels.
The book is divided into two parts, one covering lipid testing and one covering lipid management in the prevention of cardiovascular disease.

  • Sales Rank: #10051919 in Books
  • Brand: Carlson, Lars A.
  • Published on: 2012-06-30
  • Original language: English
  • Number of items: 1
  • Dimensions: 10.98" h x .38" w x 8.27" l, .0 pounds
  • Binding: Paperback
  • 144 pages

From the Back Cover
Nil

About the Author
Professor Lars A Carlson is currently Emeritus Research Professor at the Karolinska Institutet and Director of the Lipid and Hypertension Clinic at Sophiahemmet, Stockholm, Sweden. He qualified in medicine at the Karolinska Institutet, and later obtained his PhD there. His clinical training was undertaken at the Department of Internal Medicine, Karolinska Hospital. He became the first Swedish Professor of Geriatric Medicine in Uppsala and created the Department of Geriatric Medicine at Uppsala University. This was followed by positions at the Karolinska Institutet as Professor of Internal Medicine and at the Department of Internal Medicine, Karolinska Hospital as a Consultant Physician. At the same time he was Director of the King Gustaf V Research Institute, Karolinska Institutet. He has also been a Visiting Professor at the Royal Postgraduate Medical School, Hammersmith Hospital, London, and the University Department of Medicine, Hopital Cantonal, Geneva, Switzerland. Professor Carlson has been the President of the European Society for Clinical Investigation and the European Atherosclerosis Society. He has been the editor of the journal Atherosclerosis and has published some 500 scientific articles. For 20 years he has been a member of the Nobel Assembly, Karolinska Institutet. His main research interests include clinical lipidology and atherosclerosis. He received the prestigious Oscar Minkowski Prize of the European Diabetes Society and several other national and international awards for scientific achievements.

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0 of 0 people found the following review helpful.
Good and solid review of lipid metabolism and studies
By Helmut Steinberg
Good and solid review of lipid metabolism and studies. Not helpful for more complicated treatment - refer to AHA guidelines that were recently updated

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Minggu, 19 Agustus 2012

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Selasa, 14 Agustus 2012

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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics), by Gareth James, Daniela Witten, Trevor Ha

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.

Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

  • Sales Rank: #2926 in Books
  • Brand: Brand: Springer
  • Published on: 2013-08-12
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.40" h x 1.00" w x 6.40" l, 2.00 pounds
  • Binding: Hardcover
  • 426 pages
Features
  • Used Book in Good Condition

Review

“This book by James, Witten, Hastie, and Tibshirani was a great pleasure to read, and I was extremely surprised by it and the available material. In my opinion, it is the best book for teaching statistical learning approaches to undergraduate and master students in statistics. … All in all, this is a great textbook for teaching an introductory course in statistical learning. … In my opinion, there is no better book for teaching modern statistical learning at the introductory level.” (Andreas Ziegler, Biometrical Journal, Vol. 58 (3), May, 2016)

“This book has a very strong advantage that sets it well ahead of the competition when it comes to learning about machine learning: it covers all of the necessary details that one has to know in order to apply or implement a machine learning algorithm in a real-world problem. Hence, this book will definitely be of interest to readers from many fields, ranging from computer science to business administration and marketing.” (Charalambos Poullis, Computing Reviews, September, 2014)

“The book provides a good introduction to R. The code for all the statistical methods introduced in the book is carefully explained. … the book will certainly be useful to many people (including me). I will surely use many examples, labs and datasets from this book in my own lectures.” (Pierre Alquier, Mathematical Reviews, July, 2014)

“The stated purpose of this book is to facilitate the transition of statistical learning to mainstream. … it adds information by including more detail and R code to some of the topics in Elements of Statistical Learning. … I am having a lot of fun playing with the code that goes with book. I am glad that this was written.” (Mary Anne, Cats and Dogs with Data, maryannedata.com, June, 2014)

“This book (ISL) is a great Master’s level introduction to statistical learning: statistics for complex datasets. … the homework problems in ISL are at a Master’s level for students who want to learn how to use statistical learning methods to analyze data. … ISL contains 12 very valuable R labs that show how to use many of the statistical learning methods with the R package ISLR … .” (David Olive, Technometrics, Vol. 56 (2), May, 2014)

“Written by four experts of the field, this book offers an excellent entry to statistical learning to a broad audience, including those without strong background in mathematics. … The end-of-chapter exercises make the book an ideal text for�both classroom learning and self-study. … The book is suitable for anyone interested in using statistical learning tools to analyze data. It can be used as a textbook for advanced undergraduate and master’s students in statistics or related quantitative fields.” (Jianhua Z. Huang, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 19, 2014)

“It aims to introduce modern statistical learning methods to students, researchers and practitioners who are primarily interested in analysing data and want to be confined only with the implementation of the statistical methodology and subsequent interpretation of the results. … the book also demonstrates how to apply these methods using various R packages by providing detailed worked examples using interesting real data applications.” (Klaus Nordhausen, International Statistical Review, Vol. 82 (1), 2014)

“The book is structured in ten chapters covering tools for modeling and mining of complex real life data sets. … The style is suitable for undergraduates and researchers … and the understanding of concepts is facilitated by the exercises, both practical and theoretical, which accompany every chapter.” (Irina Ioana Mohorianu, zbMATH, Vol. 1281, 2014)�

"The book excels in providing the theoretical and mathematical basis for machine learning, and now at long last, a practical view with the inclusion of R programming examples. It is the latter portion of the update that I’ve been waiting for as it directly applies to my work in data science. Give the new state of this book, I’d classify it as the authoritative text for any machine learning practitioner...This is one book you need to get if you’re serious about this growing field." (Daniel Gutierrez, Inside Big Data, inside-bigdata.com, October 2013)

Review

"An Introduction to Statistical Learning (ISL)" by James, Witten, Hastie and Tibshirani is the "how to'' manual for statistical learning. Inspired by "The Elements of Statistical Learning'' (Hastie, Tibshirani and Friedman), this book provides clear and intuitive guidance on how to implement cutting edge statistical and machine learning methods. ISL makes modern methods accessible to a wide audience without requiring a background in Statistics or Computer Science. The authors give precise, practical explanations of what methods are available, and when to use them, including explicit R code. Anyone who wants to intelligently analyze complex data should own this book." (Larry Wasserman, Professor, Department of Statistics and Machine Learning Department, Carnegie Mellon University)

From the Back Cover

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.

Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Most helpful customer reviews

153 of 157 people found the following review helpful.
wonderful but watch the movie
By I Teach Typing
This is a wonderful book written by luminaries in the field. While it is not for casual consumption, it is a relatively approachable review of the state of the art for people who do not have the hardcore math needed for The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics). This book is the text for the free Winter 2014 MOOC run out of Stanford called StatLearning (sorry Amazon will not allow me to include the website). Search for the class and you can watch Drs. Hastie and Tibshirani teach the material in this book.

100 of 103 people found the following review helpful.
Excellent Practical Introduction to Learning
By Michael Tsiappoutas
The book provides the right amount of theory and practice, unlike the earlier (venerable and, by now, stable) text authored (partly) by the last two authors of this one (Elements of Statistical Learning), which was/is a little heavy on the theoretical side (at least for practitioners without a strong mathematical background). The authors make no pretense about this either. The Preface says "But ESL is intended for individuals with advanced training in the mathematical sciences. An Introduction to Statistical Learning (ISL) arose from the perceived need for a broader and less technical treatment of these topics."

ISL is neither as comprehensive nor as in-depth as ESL. It is, however, an excellent introduction to Learning due to the ability of the authors to strike a perfect balance between theory and practice. Theory is there to aim the reader as to understand the purpose and the "R Labs" at the end of each chapter are as valuable (or perhaps even more) than the end-of-chapter exercises.

ISL is an excellent choice for a two-semester advanced undergraduate (or early graduate) course, practitioners trained in classical statistics who want to enter the Learning space, and seasoned Machine Learners. It is especially helpful for getting the fundamentals down without being bogged down in heavy mathematical theory, a great way to kick-off corporate Learning units, or as an aid to help statisticians and learners communicate better.

A needed and welcome addition to the Learning literature, authored by some of the most well respected names in industry and academia. A classic in the making. Recommended unreservedly.
____________________________________________
UPDATE (12/17/2013): Two of the authors (Hastie & Tibshirani) are offering a 10-week free online course (StatLearning: Statistical Learning) based on this book found at Stanford University's Web site (Starting Jan. 21, 2014). They also say that "As of January 5, 2014, the pdf for this book will be available for free, with the consent of the publisher, on the book website." Amazing opportunity! Enjoy!
____________________________________________
UPDATE (04/03/2014): I took the course above and found it very helpful and insightful. You don't need the course to understand the book. If anything, the course videos are less detailed than the book. It is certainly nice, though, to see the actual authors explain the material. Also, the interviews by Efron and Friedman were a nice touch. The course will be offered again in the future.

35 of 37 people found the following review helpful.
cover all of your bases
By Joseph Johnson
If you want to build a comprehensive machine learning library, this would be the first book to purchase. While it does cover all of the basics, it is not watered down by any means. (I had the same fear as BK Reader) I found the following to be especially helpful;

1. Straight talk - These experts come right and say which methods work best under which circumstances. While there are many fancy algorithms covered in the book, they highlight the advantages of the simpler ones.
2. Emphasis on subjects that are not heavily addressed in most ML books - They thoroughly cover the challenges of high-dimensionality, data cleaning, and standardization. They do not limit their attention to these subjects to one chapter. They bring them up continually throughout the book.
3. Expertise - Dr. Hastie and Dr. Tibshirani are two of the thought leaders in statistical learning. You can be assured that you are learning from the best.
4. Many levels of depth - While the book does cover the basics, it is not watered down by any means. (I had the same worry as BK Reader) There is a great deal for any student of statistics; beginner or advanced.
5. R code - You are given enough code and examples to gain confidence in your ability to independently perform excellent analysis and modeling.
6. The concepts are just plain exciting! - You will feel an excitement as you discover and re-discover the algorithms they present.

The book is a standard work along with Elements of Statistical Learning and Pattern Recognition and Machine Learning (the Bayesian approach). If you enjoy the book, you may also want to consider Applied Predictive Modeling. It has the same style and approach.

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Rabu, 08 Agustus 2012

[A198.Ebook] Free PDF The New You & the Holy Spirit (Paperback) - Common, by , by (author) Andrew Wommack

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The New You Its important to understand what happened when you received Jesus as your Savior. That knowledge and understanding will keep the Word that was sown in your heart from being stolen by Satan. There is more to salvation than you have ever imagined. The forgiveness of sin was not the only thing included in your salvation. From Gods perspective, it is just the beginning, a means to an end. ...

  • Sales Rank: #5249983 in Books
  • Published on: 2012
  • Binding: Paperback
  • 115 pages

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Kamis, 02 Agustus 2012

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Applied Choice Analysis, by David A. Hensher, John M. Rose, William H. Greene

The second edition of this popular book brings students fully up to date with the latest methods and techniques in choice analysis. Comprehensive yet accessible, it offers a unique introduction to anyone interested in understanding how to model and forecast the range of choices made by individuals and groups. In addition to a complete rewrite of several chapters, new topics covered include ordered choice, scaled MNL, generalized mixed logit, latent class models, group decision making, heuristics and attribute processing strategies, expected utility theory, and prospect theoretic applications. Many additional case studies are used to illustrate the applications of choice analysis with extensive command syntax provided for all Nlogit applications and datasets available online. With its unique blend of theory, estimation, and application, this book has broad appeal to all those interested in choice modeling methods and will be a valuable resource for students as well as researchers, professionals, and consultants.

  • Sales Rank: #947002 in Books
  • Published on: 2015-08-04
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.72" h x 2.01" w x 6.85" l, 3.34 pounds
  • Binding: Paperback
  • 1216 pages

Review
"This is an enormous book, covering in extraordinary detail all the topics selected by these respected authors. It represents a substantial update and renewal of the material covered in the first edition. In my opinion it should be on the shelves of anyone dealing with discrete choice models."
Juan de Dios Ortúzar Salas, Pontificia Universidad Católica de Chile

"Choice modelling is a very active and rapidly evolving field, with applications across numerous disciplines. The first edition of Applied Choice Analysis accomplished the major task of making the breadth of work accessible to a wide audience, with hands on examples provided throughout. Nine years on, the field has developed further, and David A. Hensher, John M. Rose and William H. Greene have again performed a remarkable job in explaining these new methods without unnecessary jargon and complexity, helping to educate the next generation of choice modellers and striking exactly the right balance between theory and practice."
Stephane Hess, University of Leeds

"The new edition of this already very popular book provides substantial added value to readers. Applied choice analysis has now been extended to include all recent developments. More intuition and further clarifications have been added. The examples provided cover thoroughly the range of case study applications. This book will work perfectly as a step-by-step introduction for the neophite as well as a core reference for the practitioner. The authors have managed to strike the right balance between practicality and accuracy, without subtracting much of the econometric details."
Riccardo Scarpa, Gibson Chair for Food, Rural and Environmental Economics, Queens University Belfast

"I cannot imagine a better introduction to choice modeling. The authors manage to bring a vivid, storytelling voice to this complex topic, with language that has personality and rhythm. The various interrelated concepts and procedures that constitute choice modeling come across as simple and straightforward. An amazing feat. The ins-and-outs of a computer code are also taught along with the statistical methods. This integration of computer language within the text is unusual and highly valuable, giving readers all the steps that are needed to implement the methods on their own data."
Kenneth Train, Adjunct Professor, University of California, Berkeley

About the Author
David A. Hensher is Professor of Management, and Founding Director of the Institute of Transport and Logistics Studies (ITLS) at The University of Sydney Business School.

John M. Rose was previously Professor of Transport and Logistics Modelling at the Institute of Transport and Logistics Studies (ITLS) at the University of Sydney Business School and moved to The University of South Australia as co-director of the Institute for Choice in early March 2014.

William H. Greene is the Robert Stansky Professor of Economics at the Stern School of Business, New York University.

Most helpful customer reviews

0 of 1 people found the following review helpful.
Good book!
By Simon
Its a good book for understanding choice experiments. However, all the examples are related to transportation and marketing. Examples with environmental and private goods may help to explain some of the concepts.

0 of 2 people found the following review helpful.
Five Stars
By Adam Chagares
Very easy read for a difficult topic.

0 of 0 people found the following review helpful.
The book is only good for statisticans
By Kinderchocolate
This book is definitely not for beginners as the theories are not properly presented. I don't think anyone but experienced statisticians can understand. For example, the book covers extensively on utilities. While it's an important topic, the topic is being repeated over and over again. I'd prefer the author explain how to do a proper choice modelling with the multinomial logit model. Very hard to read, not recmmended.

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