Hammaslahti: 2010

Kamis, 30 Desember 2010

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The Inspired Warrior's Code

Your True Potential Is Within your Grasp

The Inspired Warriors Code is not just a powerful set of principles and techniques but it is so much more - it is a proven, rich and powerful approach to living that will bring you all that you desire in life and more.

Learn how to:

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The average person never comes close to fulfilling their true potential in life. They think it's 'too difficult' or too uncomfortable and by protecting themselves through this way of thinking, they are actually trapping themselves and putting chains on their life. And for 99% of people, those chains never come off...

As an ex Martial Arts *Champion*, I teach the little-known secrets of success in this book that will give you the edge in life.

Most People Will Never Discover These *SECRET* Principles to Success...

This means improving your life, your finance, health, emotions, and overall success by over 100% in just 7 days or less. Feeling trapped and that you're not fulfilling your ultimate potential will become a thing of the past when you implement these simple and easy principles!

You can create mind blowing results with my step-by-step guide in just 7 days or less, just simply copy the instructions within and apply them to your life.

Create Your Own Personal Success Road Map in Just a Few Hours... And Gain CONFIDENCE in the Process

An effective success plan is the most important thing you can have in your mind, "but it must be difficult, right?" Well... not exactly. Inside this guide, I spill the secrets from some of the secret principles of the World’s GREATS on how to go on to have a life of pure abundance.

For a complete Table of Contents, click the “Look Inside” button at the top left of the page.

This guide is only for people that want to:

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Sales Rank: #464597 in eBooks
Published on: 2013-01-22
Released on: 2013-01-22
Format: Kindle eBook

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0 of 0 people found the following review helpful.
This book can change the way you live your life!
By Rocky
Mac Attram opens his amazing book with this quote by Thomas Jefferson: "Nothing can stop the man with the right mental attitude from achieving his goal; nothing on earth can help the man with the wrong mental attitude." When I read that quote at the very beginning of this book I was excited about the journey I was about to take and this book did not disappoint me. This is not just a book to be read and pondered, but a set of principles that Mac wants you to commit to applying to your life. If you do apply these principles you will change your life for the better and begin to live more consciously and purposefully.

One of the key concepts in Mac's book is to create a "Life Blueprint" based on six "pillars". Doing this alone is valuable and makes the entire book worth the price. It is amazing how much clarity I felt after sitting down and consciously thinking about what I wanted my life to be like. Goals, or "intentions" as Max sometimes refers to them, can be powerful catalysts of change if they are well thought out and heartfelt. Through stories of his own life and others Max shows you how your limits are nothing but illusions and that you can take charge of your own life and "live intentionally".

This book is organized in a clear way, and as you work your way through the book you build knowledge about yourself and life. As I read the book I became excited about the possibilities for my own life by learning how other people have changed and grown despite their challenging circumstances.

Finally, Mac sets down a challenge for you to apply all of the things you have learned and pondered while reading the book in a final chapter called the 7x7 Challenge. By the time I'd made it to this point in the book I was excited to consciously put into practice the principles of the inspired warrior. This book is not one that you just read and put on the shelf; rather, it is a blueprint for taking control of your life and developing an action plan to be more the person you were meant to be. This is truly an inspirational book and I give it my highest, unqualified recommendation.

0 of 0 people found the following review helpful.
A great insight about much more than what we think of as a warrior
By Brian
Mac Atram has written an heartfelt and insightful that covers pretty areas of marital arts spiritual side. It's not really about martial arts but an extension of the spiritual side into a organized system of life and world view. It's maybe not really correct to call it "warrior" in the specific sense. Several examples of Ghandi's life are used, and in the deepest sense he was warrior, one who scored extra points by kicking the British out without firing a gun. The book takes into account thinks like synchronicity and a concept called Koinonia that I was unfamiliar with, which is about community building. This is one fairly short book for your Kindle that will take awhile to absorb. It's worth the price because of it's meatiness.

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Senin, 27 Desember 2010

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Rabu, 22 Desember 2010

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Sales Rank: #17262941 in Books
Published on: 1656
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G.K. Chesterton was a master essayist. But reading his essays is not just an exercise in studying a literary form at its finest, it is an encounter with timeless truths that jump off the page as fresh and powerful as the day they were written.

The only problem with Chesterton's essays is that there are too many of them. Over five thousand! For most GKC readers it is not even possible to know where to start or how to begin to approach them.

So three of the world's leading authorities on Chesterton - Dale Ahlquist, Joseph Pearce, Aidan Mackey - have joined together to select the "best" Chesterton essays, a collection that will be appreciated by both the newcomer and the seasoned student of this great 20th century man of letters.

The variety of topics are astounding: barbarians, architects, mystics, ghosts, fireworks, rain, juries, gargoyles and much more. Plus a look at Shakespeare, Dickens, Jane Austen, George MacDonald, T.S. Eliot, and the Bible. All in that inimitable, formidable but always quotable style of GKC. Even more astounding than the variety is the continuity of Chesterton's thought that ties everything together. A veritable feast for the mind and heart.

While some of the essays in this volume may be familiar, many of them are collected here for the first time, making their first appearance in over a century.

Sales Rank: #30280 in Books
Published on: 2011-10-18
Original language: English
Number of items: 1
Dimensions: 7.90" h x 1.10" w x 5.30" l, 1.05 pounds
Binding: Paperback
405 pages

About the Author
Pearce is the highly acclaimed literary biographer of many famous Christian writers.

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92 of 95 people found the following review helpful.
In Defense of Everything Else
By Gord Wilson
Chesterton wrote about a century ago, so the average reader would be no more likely to pick up a work by him than one by Dickens or Poe or Connan Doyle. But publishers have a reason to bring these books back, and with a vengeance-- they're out of copyright, and so free game. And if you did pick up a Chesterton novel with a shiny new cover, and delved into a couple pages, you wouldn't think it was written that long ago. In fact, it seems up to date, when some stories from fifty years ago seem hopelessly dated. This odd fact, in itself, explains the explosive Chesterton revival in our day-- why reading him is spreading like wildfire, helped in no small part by voracious readers and newfound friends.

Just so with the non-fiction, but to a smaller degree, for non-fiction cannot help belonging to a period, and being, in that sense, hopelessly dated. Here again, though, it happens that the particular period of GKC (Edwardian England) and our particular period have a great deal in common, and nowhere is this more evident than when reading GKC. Of course, no one is going to pick up a random book and just start reading, as they might a novel passed on by a friend. So three friends who are also friends of Chesterton's, if a century later, have ganged up to pass on their favorite bits. And yes, they are bits, for Chesterton was a master of the short essay-- yes short. In his own day, they were brief columns in newspapers, or a couple pages in magazines. Hmm, I'm thinking right about now, that might not be so bad. Most of the brief bits were later gathered into books, this being a way to sell books to readers who might have read a few columns and be thirsting for more.

So, oddly enough, anyone who quotes a short bit of Chesterton today probably got it from one of these longer collections of short bits. But who wants to track down all these non-fiction collections, which run into dozens of books in the case of such a prolific author? Someone needs to find the best brief bits in those books and drag them into one book. Someone has. Or rather, three someones have. Three someones pulled together 67 favorite bits into this 380 plus page collection (yes that averages to about 5 or so pages each), and, as in the newspapers of a hundred years ago (and some later), put them once again in the view of the casual reader. Not only that, you get brief introductions by the three someones as to why they love these essays.

I also love the essay, and was first introduced to it in "On Lying in Bed" (which ranks, I might add, as one of the best essays I've ever read). But decide for yourself, it's no. 8 in this volume. Which, incidentally, is ideal for those who've read some GKC novels and wonder if they dare try the non-fiction, and if so, where to start? Readers absolutely new to GKC might get addicted to not only Chesterton, but the form of the essay. And as for those of us who already have both addictions, we simply say "Thank You".

63 of 64 people found the following review helpful.
The perfect introduction to Chesterton's worldview
By Brandon Vogt
I'll admit what few are willing to say: it's tough to read G.K. Chesterton. Now when I say that, I'm not just talking about his complexity or abundant use of paradox, though both are certainly difficult. I'm referring to the fact that Chesterton was so unbelievably prolific that determining where to start is a real challenge. He published scores of book, hundreds of letters, and more than five thousand essays throughout the twentieth century. So where to begin?

Thankfully, for those of us who can't wade through all of his material, we now have a great solution. A trio of the world's leading Chesterton authorities--Dale Ahlquist, Joseph Pearce, and Aidan Mackey--have joined forces to collect his greatest essays into one volume, In Defense of Sanity: The Best Essays of G.K. Chesterton (Ignatius, paperback, 387 pages).

Chesterton's essays provide a great introduction to his thought. According to Ahlquist, "The breadth of G.K. Chesterton's achievement as an essayist is matched only by its depth. He is incredibly prolific and stunningly profound. Reading his essays not only provides a perfect lesson of this art form, but a lesson on everything else."

And he truly means everything else. These 67 essays cover everything from Charles Dickens to mystics to barbarians to the difference between stained glass window and fireworks. They could have easily titled the book, "G.K. Chesterton's Guide to Everything." And because the essays are only 5-6 pages each, the book is easy to pick up and read in spurts.

Orthodoxy remains Chesterton's most famous book, and his novels, mysteries, and poetry better reveal his imagination. But In Defense of Sanity offers the most complete introduction to Chesterton's worldview. It's intelligent, entertaining, and whimsical, just like Chesterton himself, and it reveals the characteristic sanity which makes him the true Apostle of Common Sense.

46 of 46 people found the following review helpful.
A Great Selection of Chesterton Essays
By Reclinator Maximus
There are very few essays in this collection that do not have the power to change one's perception of the world drastically (and for the better). Because so many others have written helpful things, I will just post the table of contents:

1. Introduction to The Defendant (The Defendant, 1901)
2. A Defence of Skeletons (The Defendant, 1901)
3. On Certain Modern Writers and the Institution of the Family (Heretics, 1905)
4. On Running After One's Hat (All Things Considered, 1908)
5. Woman (All Things Considered, 1908)
6. A Piece of Chalk (Tremendous Trifles, 1909)
7. What I Found in My Pocket (Tremendous Trifles, 1909)
8. On Lying in Bed (Tremendous Trifles, 1909)
9. The Diabolist (Tremendous Trifles, 1909)
10. The Twelve Men (Tremendous Trifles, 1909)
11. The Shop of Ghosts (Tremendous Trifles, 1909)
12. The Romantic in the Rain (A Miscellany of Men, 1912)
13. The Mad Official (A Miscellany of Men, 1912)
14. The Mystagogue (A Miscellany of Men, 1912)
15. The Architect of Spears (A Miscellany of Men, 1912)
16. Don't (Daily News, May 7, 1910)
17. The Mystery of the Mystics (Daily News, August 30, 1901)
18. A Much Repeated Repetition (Daily News, March 26, 1904)
19. The Maxims of Maxim (Daily News, February 25, 1905)
20. The Book of Job (GKC as MC, 1929)
21. Cheese (Alarms and Discursions, 1910)
22. On Gargoyles (Alarms and Discursions, 1910)
23. The Fading Fireworks (Alarms and Discursions, 1910)
24. The Furrows (Alarms and Discursions, 1910)
25. The Meaning of Dreams (Lunacy and Letters, 1958)
26. On Being Moved (Lunacy and Letters, 1958)
27. The Pickwick Papers (Appreciations and Criticisms of the Works of Charles Dickens, 1911)
28. The Bluff of the Big Shops (The Outline of Sanity, 1926)
29. On Architecture (Generally Speaking, 1928)
30. On Shakespeare (Generally Speaking, 1928)
31. The Slavery of Free Verse (Fancies vs. Fads, 1923)
32. Turning Inside Out (Fancies vs. Fads, 1923)
33. On Turnpikes and Mediævalism (All I Survey, 1933)
34. The Drift from Domesticity (The Thing, 1929)
35. On Vulgarity (Come to Think of It, 1930)
36. On a Humiliating Heresy (Come to Think of It, 1930)
37. On Original Sin (Come to Think of It, 1930)
38. On Jane Austen in the General Election (Come to Think of It, 1930)
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56. Tolerating Other Religions (Illustrated London News, May 31, 1913)
57. The Efficiency of the Police (Illustrated London News, April 1, 1922)
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60. Two Stubborn Pieces of Iron (The Common Man, 1950)
61. The Revival of Philosophy--Why? (The Common Man, 1950)
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63. Scipio and the Children (The Spice of Life, 1964)
64. The Philosophy of Islands (The Spice of Life, 1964)
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66. What Is Right with the World (The Apostle and the Wild Ducks, 1975)
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Senin, 20 Desember 2010

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Sales Rank: #3503795 in Books
Published on: 1705
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Sabtu, 18 Desember 2010

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After collecting blood smears and bone marrow aspirates for over 40 years, Dr. Doll has created the most up to date and comprehensive compilation of hematology case studies. These samples form the core of the case studies featured in this book, including benign disorders, such as hereditary spherocytosis, to neoplastic neoplasms like acute leukemia.

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FEATURES:
·   95 comprehensive case studies
·  227 full-color images
·  Up-to-date information from hands-on clinical practice

Sales Rank: #276607 in Books
Published on: 2013-11-19
Original language: English
Number of items: 1
Dimensions: 10.70" h x .40" w x 8.30" l, 1.30 pounds
Binding: Paperback
232 pages

Review
The wealth of practical information is a testament to the authors' tremendous experience in hematologic disorders. The real-world cases make the book especially interesting and informative. This is a valuable contribution to the field and an especially helpful review for hematology-oncology fellows." - Nitya Nathwani, M.D., City of Hope, on belaf of Doody's Review Service

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0 of 0 people found the following review helpful.
Good !
By M. Grados
Nice and easy to read book. On time.

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Good book for medical students and internal medicine residents
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Kamis, 16 Desember 2010

[D824.Ebook] Download PDF The Economics of Imperfect Labor Markets: Second Edition, by Tito Boeri, Jan van Ours

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Most labor economics textbooks pay little attention to actual labor markets, taking as reference a perfectly competitive market in which losing a job is not a big deal. The Economics of Imperfect Labor Markets is the only textbook to focus on imperfect labor markets and to provide a systematic framework for analyzing how labor market institutions operate. This expanded, updated, and thoroughly revised second edition includes a new chapter on labor-market discrimination; quantitative examples; data and programming files enabling users to replicate key results of the literature; exercises at the end of each chapter; and expanded technical appendixes.

The Economics of Imperfect Labor Markets examines the many institutions that affect the behavior of workers and employers in imperfect labor markets. These include minimum wages, employment protection legislation, unemployment benefits, active labor market policies, working-time regulations, family policies, equal opportunity legislation, collective bargaining, early retirement programs, education and migration policies, payroll taxes, and employment-conditional incentives. Written for advanced undergraduates and beginning graduate students, the book carefully defines and measures these institutions to accurately characterize their effects, and discusses how these institutions are today being changed by political and economic forces.

Expanded, thoroughly revised second edition
New chapter on labor-market discrimination
New quantitative examples
New data sets enabling users to replicate key results of the literature
New end-of-chapter exercises (with solutions at www.press.princeton.edu)
Expanded technical appendixes
Unique focus on institutions in imperfect labor markets
Integrated framework and systematic coverage
Self-contained chapters on each of the most important labor-market institutions

Sales Rank: #476301 in Books
Published on: 2013-09-08
Original language: English
Number of items: 1
Dimensions: 10.10" h x 1.40" w x 7.20" l, 2.50 pounds
Binding: Hardcover
464 pages

Review
Praise for the first edition:"The authors have written a very useful book aimed at providing a theoretical explanation and empirical reviews of evidence about a number of important issues in labor economics. . . . Many of the topics covered here are relevant to public policy, law, and economics, or even international economics classes. Because the chapters are more or less self-contained, it would be easy to assign one or two as part of a broader course in human resources or personnel economics. And doing so would be a good thing."--Peter Cappelli, Journal of Economic Literature

From the Back Cover

Praise for the first edition:"Understanding the role of labor market institutions is a difficult but central task. Good institutions can alleviate the adverse effects of the many imperfections that characterize labor markets. But, unfortunately, bad institutions can, and often do, make things worse. By relying on simple theory and an accumulating body of careful evidence, this book helps us think straight. An essential read for anybody interested in going beyond clichés, and understanding what institutions do and should do."--Olivier Blanchard, Massachusetts Institute of Technology

Praise for the first edition:"An invaluable survey of how policy affects the labor market, using the best of theory and empirical evidence."--Richard Layard, London School of Economics and Political Science

Praise for the first edition:"With a focus on state-of-the-art theoretical models and empirical evidence, Tito Boeri and Jan van Ours deftly explain how and when the invisible hand becomes all thumbs in the labor market. Their view of institutions as a response to imperfect markets, rather than a cause of them, is novel and overdue in labor economics textbooks."--Alan B. Krueger, Princeton University

Praise for the first edition:"By focusing on frontline policy debates, this book should hold the interest of students who often find traditional labor economics courses a bit dry."--Alan Manning, London School of Economics and Political Science

Praise for the first edition:"There is no real equivalent to this book. And, although it is an undergraduate-level textbook, it may also interest economists working at government institutions and international organizations who want an accessible review of the academic literature."--Fabien Postel-Vinay, University of Bristol

About the Author
Tito Boeri is professor of labor economics at Bocconi University in Milan and scientific director of the Fondazione Rodolfo Debenedetti. Jan van Ours is professor of labor economics at Tilburg University in the Netherlands and professorial fellow in economics at the University of Melbourne.

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Sales Rank: #2172136 in Books
Brand: Brand: Da Capo Press
Published on: 2002-09-13
Original language: English
Number of items: 1
Dimensions: 8.50" h x .57" w x 5.50" l, .66 pounds
Binding: Paperback
248 pages

Features

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An inspiring book about moving well
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[O205.Ebook] PDF Download Florence Nightingale: The Courageous Life of the Legendary Nurse, by Catherine Reef

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Florence Nightingale: The Courageous Life of the Legendary Nurse, by Catherine Reef

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Most people know Florence Nightingale was a compassionate and legendary nurse, but they don’t know her full story. This riveting biography explores the exceptional life of a woman who defied the stifling conventions of Victorian society to pursue what was considered an undesirable vocation. She is best known for her work during the Crimean War, when she vastly improved gruesome and deadly conditions and made nightly rounds to visit patients, becoming known around the world as the Lady with the Lamp. Her tireless and inspiring work continued after the war, and her modern methods in nursing became the defining standards still used today. Includes notes, bibliography, and index.

Sales Rank: #420434 in Books
Published on: 2016-11-08
Released on: 2016-11-08
Original language: English
Number of items: 1
Dimensions: 10.00" h x .68" w x 8.00" l, 1.00 pounds
Binding: Hardcover
192 pages

Review
* " With careful contextualization that sometimes goes missing from purely hagiographic presentations, this title offers a fuller picture of the effort and emotional price Nighingale paid to become a groundbreaker."
—Bulletin, STARRED review

* "A vividly written, richly layered portrait of a fascinating woman whose life and work influenced and inspired many."
—Kirkus, STARRED review

* "A captivating and inspiring study of one woman’s perseverance and the good that came from it."
—Booklist, STARRED review

"With accessible language, a linear story line, and photographs interspersed throughout, this is a great addition to any library. Recommended for students writing reports and others who want to learn about the remarkable 'Lady with the Lamp.'"
—School Library Journal

About the Author

Catherine Reef is the author of more than 40 nonfiction books, including many highly acclaimed biographies for young people. She lives in College Park, Maryland.

Most helpful customer reviews

3 of 3 people found the following review helpful.
A legend brought to life
By N. B. Kennedy
Catherine Reef's autobiography of the legendary nurse Florence Nightingale is a fine example of a young adult book whose audience has no upper limit. In straightforward prose, Ms. Reef tells the story of the young woman born into British privilege who brushed aside her social position to nurse the sick and war wounded.

I had no idea so much could be known about Florence Nightingale. I pretty much knew her as only a mythical saint -- all I knew was that she nursed wounded soldiers in the Crimean War. Ms. Reef uses a hundred or more sources to flesh out the very real human being. Each person in Nightingale's story comes to life: the mother determined that her daughter not dirty her hands and sully the family reputation; the father who weakly encourages her but retreats at the first sign of discord; the sickly sister whose jealousy and resentment festers; the extended family and high-born family friends who help the determined young woman achieve her goal.

The narrative is enlivened with quotes taken from memoirs, letters and official paperwork. Photographs and drawings aid in conjuring both the real woman and the woman the public wanted to imagine. I appreciate that the author didn't downplay Ms. Nightingale's motivation for pursuing her chosen profession. "On February 7, something happened to Flo while she was alone in her bedroom, something strange, wondrous, and mystical," the author writes. "It seemed to her that God spoke her name and called her to His service." By acknowledging Florence's faith, the author lays the strong foundation that carried her through her decades of grueling work as a nurse, a nursing administrator and the driving force in establishing nursing as a trained profession.

Ms. Reef's book isn't a complete work of hagiography. She acknowledges Florence's shortcomings -- her lack of compassion for the nurses under her charge, her harsh feelings toward her parents, her increasingly bad temper as her health declines -- and notes when Florence's medical ideas were wrong. For example, she believed, as most did at the time, that contagion was not how illness spread, that illness came from "miasma," or a stew of bad air, not from germs and bacteria. But when science proved that theory wrong, she willingly changed her mind and the curricula of her nursing schools.

All in all, this is a young adult book that should cross the aisle to the adult shelves. As with many books, the only difference I can see is that the type is larger, with more white space between the lines. I'm not sure why this should characterize a young adult book... their eyes are better than those of older folks anyway!

1 of 1 people found the following review helpful.
The Lady Who Changed The Care For Soldiers Of The War
By prisrob
My daughter has been looking for stories about women heroes for my grandson. Much of what is out there is all about the male hero. She has found a few, as have I. When I had the opportunity to read this young adult book about Florence Nightengale, I knew this was perfect for him. My grandson and I both read this book, and this is a compilation of both of our reviews.

Florence Nightengale has been a part of my history since my college days with a major in nursing. In our Nursing History classes, Florence Nightengale was a major component of the course. We knew her history as a wealthy young woman, finding her way in the world, and became a nurse in the Crimean War.
Florence took 38 other nurses with her to Turkey to help care for the British soldiers what she discovered was that the soldiers were not dying from war wounds as much as disease entities. Nightingale worked towards improvements in sanitation, nutrition, and other issues for the patients of the hospital. Nightingale kept records of the number of deaths, and the causes of deaths, so that on her return to Great Britain she could justify the need for improving conditions in hospitals.

She was not the angel of mercy to her fellow nurses. She was condescending and arrogant, but she brought a different type of Nursing to the front lines. Within the pages of this book we learn about her inner life through her letters, her diaries and the meticulous records she kept. She was the forerunner of the modern nurse.

My grandson liked this book. He is an avid reader, but did not know about the Crimean War nor Florence Nightengale. We discussed the war, and what kind of care soldiers had before Nightengale arrived. My grandson was a little shocked about the medical care, but it did give him a good background for what Florence Nightengale brought to the war and later for everyone. This is an engaging book, written for the young teen and older. We both found the book a learning experience. I learned more about the Crimean War, and my grandson was new to it all. We both would recommend this book for everyone.

Recommended. prisrob 10-14-16

'

0 of 0 people found the following review helpful.
The Story Behind The Legend
By C. Wong
Outside of knowing that Florence Nightingale was known as the Lady with the Lamp and that she worked in the British Army hospitals during the Crimean War, I knew nothing else. So I picked Florence Nightingale: The Courageous Life of the Legendary Nurse by Catherine Reef to read.

I learned that Florence Nightingale had a very difficult life because she went outside of the social norm at the time In England to work. She came from a wealthy family and was expected to marry, have children and take care of her family. She was not supposed to be interested in math, engage in the hard work of cleaning or work under deplorable conditions. She felt that she had a calling, she studied subjects not intended for the gentle sex. she worked long hours, often 20 hours a day in caring for the sick and injured.

She was different as a child, she rescued injured animals and nursed them back to health. Not bending the customs of the day disappointed her parents and caused her sister to think ill of her. She did not get the support that she wanted from her family but she went on and pushed nursing as a profession into a career of respect. She recognized the benefits of clean clothing and fresh air and left her stamp of greatness on nursing.

The author writes about Florence Nightingale objectively and gives much insight to her decisions and her beliefs. Well researched and profusely illustrated, this book gives us many insights into her character and distinguishes between the myth and the reality of this woman.

I highly recommend this to all who are interested in important figures in history.

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[B557.Ebook] PDF Download Python Machine Learning, by Sebastian Raschka

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Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics

About This Book

Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization
Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms
Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets

Who This Book Is For

If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.

What You Will Learn

Explore how to use different machine learning models to ask different questions of your data
Learn how to build neural networks using Pylearn 2 and Theano
Find out how to write clean and elegant Python code that will optimize the strength of your algorithms
Discover how to embed your machine learning model in a web application for increased accessibility
Predict continuous target outcomes using regression analysis
Uncover hidden patterns and structures in data with clustering
Organize data using effective pre-processing techniques
Get to grips with sentiment analysis to delve deeper into textual and social media data

In Detail

Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.

Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Pylearn2, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.

Style and approach

Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.

Sales Rank: #3402 in Books
Published on: 2015-09
Released on: 2015-09-23
Original language: English
Number of items: 1
Dimensions: 9.25" h x 1.03" w x 7.50" l, 1.71 pounds
Binding: Paperback
454 pages

About the Author

Sebastian Raschka

Sebastian Raschka is a PhD student at Michigan State University, who develops new computational methods in the field of computational biology. He has been ranked as the number one most influential data scientist on GitHub by Analytics Vidhya. He has a yearlong experience in Python programming and he has conducted several seminars on the practical applications of data science and machine learning. Talking and writing about data science, machine learning, and Python really motivated Sebastian to write this book in order to help people develop data-driven solutions without necessarily needing to have a machine learning background. He has also actively contributed to open source projects and methods that he implemented, which are now successfully used in machine learning competitions, such as Kaggle. In his free time, he works on models for sports predictions, and if he is not in front of the computer, he enjoys playing sports.

Most helpful customer reviews

140 of 146 people found the following review helpful.
IF YOU OWN ONE PYTHON ML BOOK, THIS SHOULD BE IT!
By Jason Wolosonovich
First some general, higher-level thoughts and comments before I dive into specifics:

MY BACKGROUND:
Data Scientist; B.S. in Economics and M.S. in Business Analytics; experienced (though by no means expert) user of Scikit-learn

OVERALL THOUGHTS:
I've purchased and read (virtually) every Machine Learning book that aims to teach the reader the basics of ML using the Scikit-learn library as the main focus. I've found them to be...less than satisfactory. The examples in other books often use ML techniques in contexts for which they are not intended to be used and/or contexts they are not used in out in the real world (among other issues I have found within them).
In stark contrast, Python Machine Learning by Sebastian Raschka is stunningly-impressive, not only for the breadth and depth of coverage, but also in the manner the information is presented to the reader.

To date, I have not encountered a book on ML that incorporates multiple levels of learning in a manner such as this. It is the textual equivalent of a Neural Network with hundreds of hidden layers running on the latest NVIDIA GPU (if that comparison is lost on you, don’t worry; it’ll all make sense by the time you finish the book).

One of the underlying (though understated) themes in the book is the importance of using visual aids where appropriate to gauge the performance of the algorithms you’re using as well as to understand exactly what is going on behind the scenes, so-to-speak. If you’re a novice user of the Matplotlib graphics library for Python, this book will greatly improve your visualization skills by the time you’re done which I found to be an added bonus.

Another underlying theme is basic optimization using the NumPy library. This is reinforced throughout the book in the examples that you code by hand. Ditto for the Pandas library. To those of you brand-new to Python, you may not fully appreciate this aspect of the book until you gain some more experience and you’ve gone through the book a few times. For those of you who are more experienced users, the examples provide an amazing amount of insight into simple ways to make your code more efficient. Indeed, “Best Practices” abound in Python Machine Learning.

As a final general thought, Sebastian is an active contributor to Scikit-learn; something I do not believe to be the case with the authors of the other books that I’ve read. In order to effectively demonstrate and communicate the power of the Scikit-learn library, you really need to be familiar with it from a fundamental level. Sebastian has this knowledge in spades and that becomes readily apparent as you progress through the book. He makes no assumption about the knowledge base of the reader—he doesn’t have to—because the book incorporates learning styles appropriate for differing skill levels (see below)

FOR BEGINNING USERS:
You may have some experience with Scikit-learn and Python, though not necessarily enough where you have developed some of the “best practices” I mentioned above; you’re still getting comfortable using the library and the Python environment. This book is definitely for you!
The best way to learn this subject is by coding examples. You could not ask for a finer book on the subject; for those just starting their ML journey, you’re in good hands with Sebastian. You’ll get an excellent, hands-on education using some of the most important ML algorithms in use today in the most popular ML library used in Python. You’ll begin to develop good habits and you’ll see from a basic level, how to actually create algorithms on your own, outside of Scikit-learn! Then after you’ve had the experience of coding the algorithm by hand, you’ll move to Scikit-learn and get even more hands-on experience. You will learn about the tried-and-true algorithms that have been around for decades as well as concepts that are still in their infancy and are considered the current state-of-the-art. And as I said, you’ll learn about them by actually using them to build ML models. You’ll see how you take a concept for a project and turn it into reality using some really fantastic algorithms.

FOR INTERMEDIATE USERS:
You are comfortable using Python and Scikit-learn and have participated (or you are considering participating) in one or more Kaggle competitions. You may have some good habits/best practices formed but you’re looking to take the next step; you may know how to take a project from the data gathering and cleaning stage to a final model, but you may not have actually done it or you aren’t sure how to properly evaluate the model you have created in the end stages; you want to gain a thorough understanding of which situations are appropriate for each of the algorithms and more importantly, which situations are NOT appropriate for each of the algorithms; you want to gain a firm knowledge of how the algorithms work and you’re curious about what the state-of-the-art concepts are. Good news!
This book is DEFINITELY for you.

There comes a time in every Data Scientist’s life when you have read everything you can find on how to structure and complete projects and you feel confident that you’re ready. Then you start and you realize during the course of a project that you suddenly have a dozen more questions:

What should I do with all of these missing values?
Should I use PCA and/or other dimensionality reduction techniques?
How many folds should I use in my Cross Validation?
Should I use Nested Cross Validation or will simple K-Fold Cross Validation suffice?
Do I need to standardize my data in order to use run a Logistic Regression algorithm?
How about with a Random Forest?
What performance metric is most appropriate for my model?
What is L1 and L2 regularization (again) and when should I use it?

If you have ever asked yourself any of these questions, rest assured this book will become your go-to reference for these questions as well as questions that you haven’t even thought of yet. Sebastian will fill in the gaps in your knowledge and you’ll gain the confidence to tackle the projects you have been looking forward working on all this time.

FOR ADVANCED USERS:
Much of the information in this book may be familiar to you, however the mathematical concepts behind the algorithms may not be. You may be interested in reading the seminal research on each of the concepts presented in the book. Sebastian has you covered as well. He provides symbolic mathematical proofs for those so-inclined, as well as a multitude of citations for where you can find the research that supports and/or explores the concepts more thoroughly. The book is well-researched and cited and the concepts are given very thorough treatment.

TL;DR (SUMMARY):
I realize the experience levels described above are subjective. They are present merely to serve as reference points for the readers and to underscore my belief that Python Machine Learning has something for virtually every skill level. I cannot recommend this book more highly!

BONUS - Topics/Algorithms Covered Throughout the Book (there are a TON!):

Perceptron
Adaline
Stochastic Gradient Descent (SGD)
Support Vector Machines (SVM)
Logistic Regression
Difference between L1 and L2 regularization (with excellent graphics showing the difference)
Out-of-core/online learning (truly Big Data)
The Kernel Trick
Parameter Optimization
Random Forest Classifier
Parametric vs. Non-parametric (and which are which)
K-Nearest Neighbors (KNN)
Bias/Variance Trade off (great graphics showing the difference)
Decision Trees
Standardization (Data Preprocessing)
Scaling (Data Preprocessing)
Correct Mapping of data types for use in Scikit-learn algorithms
Over/Under fitting
Sequential Forward Selection (Feature Selection)
Sequential Backward Selection (Feature Selection)
Feature Importances using Random Forests (Feature Selection)
Common pitfalls (“gotchas”) that can arise with use of Random Forests
Principal Component Analysis (PCA)
Latent Discriminant Analysis (LDA – this topic is almost never covered in similar books)
Kernel PCA + caveats for its use
Use of Pipelines in Scikit-learn for streamlining the modeling process (this never gets coverage and is a big efficiency boost)
Cross Validation (K Fold)
Nested Cross Validation
Common Metrics for Model Evaluation and how to graph each to gauge performance
Ensemble Methods (Majority Voting Classifier)
Plotting Decision Boundaries (important for gaining insight into ensemble performance)
Bootstrap Aggregating (Bagging)
Boosting
Sentiment Analysis using bag-of-words model
Sentiment Analysis using SGD Classifier and Out-of-Core learning to analyze large document datasets via streaming/mini-batching for Data that is too large to fit in memory at once
Embedding Machine Learning algorithms into web applications using the web framework called Flask—this is a hot skill to have in the job market
Regression Analysis for Continuous Target Variables
Aesthetic adjustments/extensions to Matplotlib graphs using the Seaborn library
RANSAC Regression
Dealing with non-linear relationships in the context of Regression (Data Transformations)
Clustering (K-Means, Agglomerative, Divisive)
Visualizing clusters
Hard vs. Soft clustering
The “Elbow” method for clustering
DBSCAN clustering
Common “gotchas” to be aware of when using clustering algorithms
Artificial Neural Networks (ANN)
Multi-Layer Perceptron (MLP) Neural Net
Forward Propagation
Backward Propagation
Using the Theano library to run Neural Networks on Graphical Processing Units (GPU)—this is an extremely hot topic and demonstrates the timelessness of many of these algorithms.

38 of 40 people found the following review helpful.
My new #1 Python ML book!
By BRIAN M THOMAS
This is a fantastic book, even for a relative beginner to machine learning such as myself. The first thing that comes to mind after reading this book is that it was the perfect blend (for me at least) of theory and practice, as well as breadth and depth.

Let’s face it, we know that machine learning isn’t an easy subject. You need theory…but you also need practice in the form of some serious coding before you really start understanding it. And this is one area where Sebastian’s book shines: it contains a plethora of really good code examples that are illuminating and well explained, and which cover a very wide range of different machine learning algorithms. And, speaking of code, as another reviewer has pointed out, another huge plus is that, in many places, Sebastian shows you how to gauge the performance of your code and make it more efficient.

For me, the best measure of any book such as this is how many “ah ha!” moments I had while reading it. And I had more than a few while reading Sebastian’s book. One such “ah ha!” moment came while reading chapter 12 (and this also illustrates that nice blend of theory and practice I already mentioned above). In this particular chapter, he discusses training artificial neural networks for image recognition. At the heart of this approach is back propagation, which is pretty much THE bread and butter behind multilayered neural networks. He presents a detailed discussion of back propagation in two separate pieces: one that is intuitive and “top down”; the other a more mathematical, “bottoms up” approach that goes through the algorithm step by step, showing how the gradients are computed and the weights updated. His treatment of back propagation was one of the better explanations I’ve seen and really cleared things up for me.

One last thing I must mention: at the time of release, this was the first machine learning book for Python (to my knowledge) that has an entire chapter devoted to Theano, which he uses to parallelize neural network training. For those who don’t know, Theano is a particularly nice (not to mention very powerful) Python library for doing machine learning, most especially if you can utilize the power of GPU computing. In addition, that particular chapter (13) also introduces the brand new Python library named Keras, which is built on top of Theano and is a really nice library for the rapid building and prototyping of neural networks (in the spirit of Torch). Being a brand new library, his treatment of Keras was necessarily brief, but it was a great starting point.

In conclusion, I am very confident that if you do pick up this book, you won’t be at all disappointed. And be sure and grab the accompanying code for the book on his GitHub repository (just look for “python-machine-learning-book” on github.com/rasbt.) His code is top notch and I’ve yet to encounter any problems with it.

41 of 45 people found the following review helpful.
I'm Now a Fanboy
By Perry Nally
Technical, but not too much. Let's face it, machine learning algorithms are technical in nature. However, this book allows you to gloss over the actual technical details if you don't really need to understand them right away and view the implementation of the logic in the code snippets. Though, I must say, the presentation of the technical subjects are explained clearly and with supporting graphs and images to help visualize the concepts. It was a wonderful experience to understand the code, even though the theory was also given. This allows most people to jump right in and start writing in python. For the mathematicians out there, you can take the equations and verify them if need be.

The ideas build upon each other and just like teaching a child to talk, the quality of machine learning seems to be about getting good training sets for your algorithms. As such, Sebastian is good about giving in-depth, best practice steps on how to make sure your training data is clean and normalized, as well as your feature selection is relevant - which was great. You'll learn how to merge results from multiple data sets into a more thorough model in order to filter out weaknesses of various algorithms. You'll be able to predict future outcomes using regression analysis using techniques from statistics to look for patterns and anomalies, again, all explained in very understandable words. Though the content and speed of the book is all very good and relevant, the icing on the cake is in the last two chapters (which you need to have worked up to in the previous chapters); understanding and then creating a layered neural network to solve complex problems like hand written digit recognition. And to top it all off he teaches us how to make it more powerful using the Theano tool.

You also gain great insight into many uses of the python language, SQLite databases, implement it by developing a small web application during the process, and understanding some parallel processing - from loading large data sets and processing them to using math and science libraries to process the data without having to be a rocket scientist.

Another great benefit of this read is not just the programming and math techniques you'll learn, but the right questions you need to ask about your data to make the results useful - unsupervised learning. The data sets used in the book range from breast cancer subjects to political science and from movie reviews to processing topics in order to determine a particular bias and then on to image processing.

The only downside (if you can even call it that) is that there is a lot of math involved, but to his credit, Sebastian teaches it in such a way that you don't really need to understand the math equation to understand how the equation works. In essence he is saying, "You don't need to understand the laws of physics to build a house, but here are a set of tools to help you create a magnificent house."

The fundamental concepts I've learned have opened the door to an enormous amount of possibilities I could not have even thought of doing had I not read this book. I used to think that true machine learning was only for super geniuses. But now I feel like I have another set of tools I can use to perform nearly superhero tasks. Python Machine Learning will be a reference book I use for many years to come.

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