Minggu, 29 September 2013

[E266.Ebook] Fee Download Pattern Classification (Pt.1), by Richard O. Duda, Peter E. Hart, David G. Stork

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Pattern Classification (Pt.1), by Richard O. Duda, Peter E. Hart, David G. Stork

The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

  • Sales Rank: #118538 in Books
  • Brand: Brand: Wiley
  • Published on: 2000-11-09
  • Original language: English
  • Number of items: 1
  • Dimensions: 10.30" h x 1.18" w x 7.30" l, 2.75 pounds
  • Binding: Hardcover
  • 680 pages
Features
  • Used Book in Good Condition

Review
"…it provides a good introduction to the subject of Pattern Classification." (Journal of Classification, September 2007)

"…a fantastic book! The presentation...could not be better, and I recommend that future authors consider…this book as a role model." (Journal of Statistical Computation and Simulation, March 2006)

"...strongly recommended both as a professional reference and as a text for students..." (Technometrics, February 2002)

"...provides information needed to choose the most appropriate of the many available technique for a given class of problems." (SciTech Book News, Vol. 25, No. 2, June 2001)

"I do not believe anybody wishing to teach or do serious work on Pattern Recognition can ignore this book, as it is the sort of book one wishes to find the time to read from cover to cover!" (Pattern Analysis & Applications Journal, 2001)

"This book is the unique text/professional reference for any serious student or worker in the field of pattern recognition." (Mathematical Reviews, Issue 2001k)

"...gives a systematic overview about the major topics in pattern recognition, based whenever possible on fundamental principles." (Zentralblatt MATH, Vol. 968, 2001/18)

"attractively presented and readable" (Journal of Classification, Vol.18, No.2 2001)

From the Back Cover
From the reviews . . .

"The first edition of this book, published 30 years ago by Duda and Hart, has been a defining book for the field of Pattern Recognition. Stork has done a superb job of updating the book. He has undertaken a monumental task of sifting through 30 years of material in a rapidly growing field and presented another snapshot of the field, determining what will be of importance for the next 30 years and incorporating it into this second edition. The style is easy to read as in the original book and the statistical, mathematical material comes alive with many new illustrations. The end result is harmonious, leading the reader through many new topics..."
–Sargur N. Srihari, PhD, Director, Center for Excellence in Document Analysis and Recognition, Distinguished Professor, Department of Computer Science and Engineering, SUNY at Buffalo

Practitioners developing or investigating pattern recognition systems in such diverse application areas as speech recognition, optical character recognition, image processing, or signal analysis, often face the difficult task of having to decide among a bewildering array of available techniques. This unique text/professional reference provides the information you need to choose the most appropriate method for a given class of problems, presenting an in-depth, systematic account of the major topics in pattern recognition today. A new edition of a classic work that helped define the field for over a quarter century, this practical book updates and expands the original work, focusing on pattern classification and the immense progress it has experienced in recent years. Special features include:

  • Clear explanations of both classical and new methods, including neural networks, stochastic methods, genetic algorithms, and theory of learning
  • Over 350 high-quality, two-color illustrations highlighting various concepts
  • Numerous worked examples
  • Pseudocode for pattern recognition algorithms
  • Expanded problems, keyed specifically to the text
  • Complete exercises, linked to the text
  • Algorithms to explain specific pattern-recognition and learning techniques
  • Historical remarks and important references at the end of chapters
  • Appendices covering the necessary mathematical background

NOTE: Computer Manual in MATLAB to Accompany Pattern Classification, 2e users access toolbox via ftp://ftp.wiley.com/public/sci_tech_med/pattern_classification/ (Note: Visitors will require a password from the Manual to access.)

About the Author
RICHARD O. DUDA, PhD, is Professor in the Electrical Engineering Department at San Jose State University, San Jose, California.

PETER E. HART, PhD, is Chief Executive Officer and President of Ricoh Innovations, Inc. in Menlo Park, California.

DAVID G. STORK, PhD, is Chief Scientist, also at Ricoh Innovations, Inc.

Most helpful customer reviews

35 of 35 people found the following review helpful.
excellent revision of a classical text on statistical pattern recognition
By Michael R. Chernick
The 1973 book by Duda and Hart was a classic. It surveyed the literature on pattern classification and scene analysis and provided the practitioner with wonderful insight and exposition of the subject. In the intervening 28 years the field has exploded and there has been an enormous increase in technical approaches and applications.
With this in mind the authors and their new coauthor David Stork go about the task of providing a revision. True to the goals of the original the authors undertake to describe pattern recognition under a variety of topics and with several available methods to cover each topic. Important new areas are covered and old but now deemed less significant are dropped. Advances in statistical computing and computing in general also dictate the topics. So although the authors are the same and the title is almost the same (note that scene analysis is dropped from the title) it is more like an entirely new book on the subject rthan a revision of the old. For a revision, I would expect to see mostly the same chapters with the same titles and only a few new chapters along with expansion of old chapters.

Although I view this as a new book, that is not necessarily bad. In fact it may be viewed as a strength of the book. It maintains the style and clarity of the original that we all loved but represents the state-of-the-art in pattern recognition at the beginning of the 21st Century.

The original had some very nice pictures. I liked some of them so much that I used them with permission in the section on classification error rate estimation in my bootstrap book. This edition goes much further with beautiful graphics including many nice three-dimensional color pictures like the one on the cover page.

The standard classical material is covered in the first five chapters with new material included (e.g. the EM algorithm and hidden markov models in Chapter 3). Chapter 6 covers multilayer neural networks (a totally new area). Nonmetric methods including decision trees and the CART methodology are covered in Chapter 8. Each chapter has a large number of relevant references and many homework exercises and computer exercises.

Chapter 9 is "Algorithm-Independent Machine Learning" and it includes the wonderful "No Free Lunch" theorem (Theorem 9.1), a discussion of the minimum desciption length principle, overfitting issues and Occam's razor, bias - variance tradeoffs,resampling method for estimation and classifier evaluation, and ideas about combining classifiers.

Chapter 10 is on unsurpervised learning and clustering. In addition to the traditional techniques covered in the first edition the authors include the many advances in mixture models.

I was particularly interested in that part of Chapter 9. There is good coverage of the topics and they provide a number of good references. However, I was a bit disappointed with the cursory treatment of bootstrap estimation of classification accuracy (section 9.6.3 on pages 485 - 486). I particularly disagree with the simplistic statement "In practice, the high computational complexity of bootstrap estimation of classifier accuracy is rarely worth possible improvements in that estimate (Section 9.5.1)". On the other hand, the book is one of the first to cover the newer and also promising resampling approaches called "Bagging" and "Boosting" that these authors seem to favor.

Davison and Hinkley's bootstrap text is mentioned for its practical applications and guidance for bootstrapping. The authors overlook Shao and Tu which offers more in the way of guidance. Also my book provides some guidance for error rate estimation but is overlooked.

My book also illustrate the limitations of the bootstrap. Phil Good's book provides guidance and is mentioned by the authors. But his book is very superficial and overgeneralized with respect to guiding practitioners. For these reasons I held back my enthusiasm and only gave this text four stars.

0 of 0 people found the following review helpful.
Great quality!
By Amazon Customer
The book seems to be bearly used at all. Great quality. Arrived on time as well. No complaints at all

29 of 34 people found the following review helpful.
A Very Bad Sequel
By Book Runner
I have now used this book 3 times for a class. While the 1st edition did a nice job of covering the material in its time, the additions to in the 2nd addition are a disaster. What the book has going for it is that it at least lists the necessary material for such a course in the table of contents. However, all the additional material is poorly explained at best. The problem sets are too few and the ones that are included are generally weak.

I have tried to use this book, but after constant student complaints and my own difficulty with the text, I have finally concluded that the problem lies with the text and not with the users.

I think an indicator of problems was the large number of errors in the first printing; large here is an understatement. Even in later additions, the 4th, the size of the errata is huge. I think this is indicative of the authors' attention to detail and seriousness in preparation. I have found similar errors and ambiguities in the associate Computer Manual.

The bottom line is that this book has seen its final appearance in our curriculum. I would use any other text, even an older one.

There is simply not enough room or time to point out all the problems with this text. Do yourself a favor if considering this text for a class. Don't bother.

See all 41 customer reviews...

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Kamis, 26 September 2013

[H314.Ebook] Free PDF Getting Started with Amazon Redshift, by Stefan Bauer

Free PDF Getting Started with Amazon Redshift, by Stefan Bauer

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Getting Started with Amazon Redshift, by Stefan Bauer

Getting Started with Amazon Redshift, by Stefan Bauer



Getting Started with Amazon Redshift, by Stefan Bauer

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Getting Started with Amazon Redshift, by Stefan Bauer

Start by learning the fundamentals and then progress to creating and managing your own Redshift cluster. This guide walks you step-by-step through the world of big data, cloud computing, and scalable data warehousing.

Overview

  • Step-by-step instructions to create and manage your Redshift cluster
  • Understand the technology behind the database engine, as you learn about compression, block level storage, and column stores
  • Learn the implementation and database design considerations you will need to understand to successfully implement your own Amazon Redshift cluster

In Detail

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service. It provides an excellent approach to analyzing all your data using your existing business intelligence tools.

Getting Started With Amazon Redshift is an easy-to-read, descriptive guide that breaks down the complex topics of data warehousing and Amazon Redshift. You will learn the fundamentals of Redshift technology and how to implement your own Redshift cluster, through practical, real-world examples. This exciting new technology is a powerful tool in your arsenal of data management and this book is a must-have to implement and manage your next enterprise Data Warehouse.

Packed with detailed descriptions, diagrams, and explanations, Getting Started With Amazon Redshift will bring you along, regardless of your current level of understanding, to a point where you will feel comfortable with running your own Redshift cluster. The author's own experiences will give you an understanding of what you will need to consider when working with your own data. You will also learn about how compression has been implemented and what that means relative to a column store database structure. As you progress, you will gain an understanding of monitoring techniques, performance considerations, and what it will take to successfully run your Amazon Redshift cluster on a day-to-day basis. There truly is something in this book for everyone who is interested in learning about this technology.

What you will learn from this book

  • Provision your own Redshift cluster
  • Connect third party tools and software to your Redshift cluster
  • Load data using Redshift's copy tools and manage your data files
  • Manage queries through the implementation of Workload Management
  • Gain an understanding of the underlying architecture, everything from a detailed view of compression, to column store block-level storage
  • Resize your cluster and use Redshift scalability to expand and grow with ease as your data storage needs grow

Approach

Getting Started With Amazon Redshift is a step-by-step, practical guide to the world of Redshift. Learn to load, manage, and query data on Redshift.

Who this book is written for

This book is for CIOs, enterprise architects, developers, and anyone else who needs to get familiar with RedShift. The CIO will gain an understanding of what their technical staff is working on; the technical implementation personnel will get an in-depth view of the technology, and what it will take to implement their own solutions.

  • Sales Rank: #710698 in Books
  • Published on: 2013-06-14
  • Released on: 2013-06-14
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.25" h x .35" w x 7.50" l, .61 pounds
  • Binding: Paperback
  • 154 pages

About the Author

Stefan Bauer

Stefan Bauer has worked in business intelligence and data warehousing since the late 1990s on a variety of platforms in a variety of industries. Stefan has worked with most major databases, including Oracle, Informix, SQL Server, and Amazon Redshift as well as other data storage models, such as Hadoop. Stefan provides insight into hardware architecture, database modeling, as well as developing in a variety of ETL and BI tools, including Integration Services, Informatica, Analysis Services, Reporting Services, Pentaho, and others. In addition to traditional development, Stefan enjoys teaching topics on architecture, database administration, and performance tuning. Redshift is a natural extension fit for Stefan's broad understanding of database technologies and how they relate to building enterprise-class data warehouses.

Most helpful customer reviews

5 of 5 people found the following review helpful.
More than a glossy review..
By Alan Williamson
Amazon have done it again and set the bar extremely high with their initial warehouse-in-the-cloud offering. RedShift has delivered a product at a price point that will leave many an enterprise wondering why they have just signed that 6 figure purchase order to Microsoft/Oracle or IBM.

This book is a fantastic overview on Redshift and the power it can bring.

Beautifully articulated, taking the reader through the whole process from initial cluster creation, to data loading, querying and monitoring (he labored on that one quite a bit).

There is a great piece on the different types of compression that I found interesting and while I know most of them, I haven't read them explained in such an easy to understand way before.

4 of 4 people found the following review helpful.
Practical Introduction to Amazon Redshift
By Hank
Stefan Bauer's Getting Started with Amazon Redshift is a practical introduction into how you might use Amazon Redshift. Although not exactly a step-by-step how-to tutorial, Bauer delivers plenty of details on what you need to do, how you should do it and why you should consider what you are about to do. If you want someone to hold your hand so you can claim you used Redshift, this book might not meet your needs. If you already have some data management experience, you will appreciate Bauer sharing his challenges and excitement with Amazon Redshift's powerful capabilities.

Bauer's explanation for why a columnar database matters is the best I ever read. His conversational style makes this book easy to read and understand. He balances the existing strengths of Amazon Redshift with the rapidly evolving enhancements and tool partnerships. His description of his day-to-day experiences delivers far more value than any sales demonstration.

I learned a lot from this book and recommended it to my colleagues. If you are interested in the practical usage of Amazon Redshift, I also recommend this book to you.

2 of 2 people found the following review helpful.
A talkative coverage of Amazon Redshift
By John Rotenstein
All of the official documentation for Redshift is available for free from Amazon, so this book is not attempting to be an official user manual for Redshift. Rather, it is passing information to the reader in a friendly manner, with additional commentary on how things differ from other systems on the market. This is helpful, since the official documentation focuses more on what Redshift does, while this book also highlights what it doesn't do (such as unsupported SQL commands). The book also makes it easier to come up-to-speed with Redshift because it is being explained by someone who has already had to 'climb the learning curve' and is now explaining this in a less-formal manner, with frequent emphasis on difficult or 'different than normal' topics.

The author's style is informal and friendly, but sometimes overly talkative. For example, there are some paragraphs that occupy a whole page and sound like they were written for a blog, without much formal editing. Many concepts are thrown in without a lot of background, so it may be difficult for somebody without much previous experience in databases and data warehousing, but the typical reader who is interested in learning about Redshift probably comes from such a background anyway.

If you're looking to learn Redshift and you've found the official documentation a bit dry or difficult, then this book will give you similar information in a friendly and more 'personal' manner. Please note that, as an online product, new features are continually being added to Redshift so some portions of this book are already outdated.

Here's a quick outline of the book:

CHAPTER 1: OVERVIEW
The book begins with a fairly informal chat about Redshift, its pricing and how it will likely affect the Data Warehouse marketplace.

CHAPTER 2: TRANSITION TO REDSHIFT
This chapter talks through the creation of a Redshift cluster and then gets down into technical detail, showing what standard SQL functions are NOT supported by Redshift. It also covers accessing Redshift via command-line and via SQL tools.

CHAPTER 3: LOADING YOUR DATA INTO REDSHIFT
As the author says, "this is where the fun starts". Topics include schema and table creation, loading data from Amazon S3 (which was the only method available at the time of publishing), plus a bit on performance monitoring and tips on optimising table design (using Redshift's Sort and Distribution Keys). Truth be told, data loading is where typical Redshift users end up spending most of their time.

CHAPTER 4: MANAGING YOUR DATA
This covers snapshots, resizing, vacuuming of tables and workload management (which is the low-level management of job queues). These topics are important once your cluster is up and running and you'd like to improve performance or move into 'production' mode for your system.

CHAPTER 5: QUERYING DATA
Not so much a lesson in SQL, but rather information for people already familiar with SQL but considering a move to Redshift. Special tables and the EXPLAIN command are covered, plus tips on JOINs, INSERTs, etc. You won't learn data warehousing from this chapter, but if you're familiar with an existing system then you'll come to understand the subtle differences with Redshift. Some SQL code samples are included in this chapter.

CHAPTER 6: BEST PRACTICES
This final chapter is a random collection of remaining topics such as security and monitoring

See all 12 customer reviews...

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Minggu, 22 September 2013

[I837.Ebook] Fee Download Animal Farm (MAXNotes Literature Guides), by Joseph E. Scalia

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REA's MAXnotes for George Orwell's Animal Farm

MAXnotes offer a fresh look at masterpieces of literature, presented in a lively and interesting fashion. Written by literary experts who currently teach the subject, MAXnotes will enhance your understanding and enjoyment of the work. MAXnotes are designed to stimulate independent thought about the literary work by raising various issues and thought-provoking ideas and questions.

MAXnotes cover the essentials of what one should know about each work, including an overall summary, character lists, an explanation and discussion of the plot, the work's historical context, illustrations to convey the mood of the work, and a biography of the author. Each chapter is individually summarized and analyzed, and has study questions and answers.

  • Sales Rank: #1196660 in Books
  • Brand: Brand: Research n Education Association
  • Published on: 1995-03-01
  • Released on: 1995-03-01
  • Original language: English
  • Number of items: 1
  • Dimensions: 8.30" h x .23" w x 5.30" l, .25 pounds
  • Binding: Paperback
  • 96 pages
Features
  • Used Book in Good Condition

From the Back Cover
REA’s MAXnotes is an insightful series of literature study guides covering over 80 of the most popular literary works.

MAXnotes study guides are student friendly and provide all the essentials needed to prepare students for homework, discussions, reports, and exams.

Our MAXnotes for George Orwell’s Animal Farm study guide includes an overall summary, character lists, explanation and discussion of the plot, overview of the work’s historical context, and a biography of the author. Each section of the work is individually summarized and includes study questions and answers.

Our George Orwell’s Animal Farm MAXnotes study guide is a handy resource when preparing for exams or doing homework, and it makes a great companion to the original work.

George Orwell’s Animal Farm MAXnotes is also an invaluable resource for English teachers who are teaching the original work and need a refresher. Each MAXnotes includes topics for term papers with sample outlines.

 

About the Author
Joseph Scalia is a psychotherapist who has written articles for "The Journal of Interpersonal Violence" and "Modern Psychoanalyst."

Most helpful customer reviews

0 of 0 people found the following review helpful.
Four Stars
By Anonymous
Very helpful!

5 of 7 people found the following review helpful.
Exellent!!
By A Customer
I am in eighth grade and we just read this book. It is very good, and I enjoy how it depicts the Russian Revolution. It is neat how each of the animals represents a real character from history. It is a wonderful way to put the concept of the Russian Revolution into perspective and make it easy to understand, far better than reading a history book could. The person who said "not a great choice" must have not understood the book correctly, or perhaps the concept was beyond her understanding, because only then could I see how one could not enjoy it. Definatly, if you read this book, you should wait until and LEAST eighth grade, preferably tenth, or you probably wont enjoy it. I read it in sixth grade and hated it, and then again in eighth grade and thought that it was exellent!

2 of 6 people found the following review helpful.
Not a Great Choice
By A Customer
The book was a little differnent than what I was expecting. I mean who thinks that animals will actually take over things. The book was a little too bizarre for that subject. Orwell also tried to act as if it were a revolution like the Russain Revolution. I was totally lost personally! I thought that it was a horrible book. No wonder high schoolers hate reading!

See all 9 customer reviews...

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Validate your AWS skills. 

This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud.  AWS has been the frontrunner in cloud computing products and services, and the AWS Certified Solutions Architect Official Study Guide for the Associate exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, access to Sybex’s interactive online learning environment, and much more. This official study guide, written by AWS experts, covers exam concepts, and provides key review on exam topics, including:

  • Mapping Multi-Tier Architectures to AWS Services, such as web/app servers, firewalls, caches and load balancers
  • Understanding managed RDBMS through AWS RDS (MySQL, Oracle, SQL Server, Postgres, Aurora)
  • Understanding Loose Coupling and Stateless Systems
  • Comparing Different Consistency Models in AWS Services
  • Understanding how AWS CloudFront can make your application more cost efficient, faster and secure
  • Implementing Route tables, Access Control Lists, Firewalls, NAT, and DNS
  • Applying AWS Security Features along with traditional Information and Application Security
  • Using Compute, Networking, Storage, and Database AWS services
  • Architecting Large Scale Distributed Systems
  • Understanding of Elasticity and Scalability Concepts
  • Understanding of Network Technologies Relating to AWS
  • Deploying and Managing Services with tools such as CloudFormation, OpsWorks and Elastic Beanstalk.

Learn from the AWS subject-matter experts, review with proven study tools, and apply real-world scenarios. If you are looking to take the AWS Certified Solutions Architect Associate exam, this guide is what you need for comprehensive content and robust study tools that will help you gain the edge on exam day and throughout your career. 

  • Sales Rank: #5486 in Books
  • Published on: 2016-10-17
  • Original language: English
  • Dimensions: 9.10" h x 1.00" w x 7.20" l, .0 pounds
  • Binding: Paperback
  • 504 pages

From the Back Cover

Covers exam objectives, including designing highly available, cost efficient, fault tolerant, scalable systems, implementation and deployment, data security, troubleshooting, and much more....

Includes interactive online learning environment and study tools with: + 2 custom practice exams
+ More than 100 electronic flashcards
+ Searchable key term glossary

Your complete guide to preparing for the AWS Certified Solutions Architect — Associate Exam

The AWS Certified Solutions Architect Official Study Guide is your one-stop resource for coverage of the Associate Level Exam. This Sybex Study Guide covers the Associate Exam objectives. You'll prepare smarter and faster with Sybex thanks to expert content, including assessment tests that check your exam readiness, an objective map, real-world scenarios, hands-on exercises, key topic exam essentials, and challenging chapter review questions. Reinforce what you have learned with the Sybex online learning environment and test bank, accessible across multiple devices. Get prepared for the AWS Associate Level Exam today.

Coverage of the exam objectives in this Study Guide means you'll be ready for:

  • Mapping Multi-Tier Architectures to AWS Services, such as web/app servers, firewalls, caches, and load balancers
  • Understanding managed RDBMS through AWS RDS (MySQL®, Oracle®, SQL Server®, Postgres, Aurora)
  • Understanding Loose Coupling and Stateless Systems
  • Comparing Different Consistency Models in AWS Services
  • Understanding how AWS CloudFront can make your application more cost efficient, faster, and secure
  • Implementing Route tables, Access Control Lists, Firewalls, NAT, and DNS
  • Applying AWS Security Features along with traditional Information and Application Security
  • Using Compute, Networking, Storage, and Database AWS services
  • Architecting Large Scale Distributed Systems
  • Understanding of Elasticity and Scalability Concepts
  • Understanding of Network Technologies Relating to AWS
  • Deploying and Managing Services with tools such as CloudFormation, OpsWorks, and Elastic Beanstalk

Interactive learning environment

Take your exam prep to the next level with Sybex's superior interactive online tools. To access our interactive learning environment simply visit www.wiley.com/go/sybextestprep type in your unique PIN, and instantly gain access to:

  • Interactive test bank with 2 custom practice exams helps you identify where you need additional study. Practice exams help you identify areas where further review is needed. Get more than 90% of the answers correct, and you're ready to take the certification exam. 100 questions total!
  • More than 100 electronic flashcards to reinforce learning and last-minute prep before the exam
  • Comprehensive glossary in PDF format gives you instant access to the key terms so you are fully prepared

AWS Certification

AWS Certifications recognize IT professionals with the technical skills and expertise to design, deploy, and operate applications and infrastructure on AWS. Exams are offered in multiple languages at testing centers around the world.

The AWS Certified Solutions Architect – Associate Exam is intended for individuals with experience designing distributed applications and systems on the AWS Cloud.

Most helpful customer reviews

49 of 52 people found the following review helpful.
Seems like it was written for an outdated version of the AWS site that is served to old clients
By rpgmaker
There's something you need to be aware about this book if you're new to AWS. It seems that it is either outdated (improvable given that it was released just a couple of days ago, but maybe they started to be write it years ago and released just now..) or it was written with an outdated version of the AWS site that is served to old AWS clients, which would be understandable if you read the authors bio at the beginning but it's an unforgivable editing oversight since the reader isn't warned about this. I'm just starting but there have been several assumptions made in the book that are just weird. For example they keep telling you to choose either EC2-VPC or EC2-Classic but EC2-Classic isn't available for new clients anymore and they don't tell you this in the book.

So far it's a good book and I will update this score when I finish reading it or find another way to contact the authors (I found no contact information regarding errata listed in the book). I was waiting to finish the book before posting but I thought I should let everyone know before everything else is drowned out by the 5 stars reviews written by people that haven't finished reading it either.

10 of 10 people found the following review helpful.
Essential Book to pass the certification
By Alex
Excellent material! I passed the certification exam just by reading it and completing the quizzes and flashcards.
Register for the quizzes and flashcards as instructed in the first pages

4 of 4 people found the following review helpful.
Good as reference, lot of questions, some details to improve though
By Celestino
Cons:
- I have to agree with one of the reviews above, there are things that are outdated or even discontinued, seems they wrote few chapters long ago and others just a month ago.
- In my opinion something worth to mention is the way they wrote the Security chapter (12). This was rather confusing if you compare with the rest of the book, e.g. they mention a service, and instead to highlight the security features use two paragraphs to describe the service and how works, advantages, etc. ( when this was already explained in previous chapters), may be good to refresh your knowledge, although in my case make me lost focus a bit. Some parts on this chapter are literally a "copy&paste" of the AWS security whitepaper, maybe that is the reason. Even in the summary part they also do the same a bit, Exam Essentials are OK though.
- The exercises are too simple or too generic, with not much explanation and referring to amazon manuals.

Pros:
- One value of this book is that it comes with the exams and a fair amount of questions.
- Is a good complement to study or to get into AWS
- Most of the book is a good digested version of whitepapers and official documentation
- The fact to be the "official study guide" wrote by some people related to the exam may give you some piece of mind when going to the test :)

See all 13 customer reviews...

AWS Certified Solutions Architect Official Study Guide: Associate Exam, by Joe Baron, Hisham Baz, Tim Bixler, Biff Gaut, Kevin E. Kelly, S PDF
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  • Sales Rank: #4466183 in Books
  • Published on: 2009-08-30
  • Original language: Spanish
  • Dimensions: 9.50" h x 7.75" w x 1.25" l, 2.84 pounds
  • Binding: Hardcover
  • 554 pages

Most helpful customer reviews

0 of 0 people found the following review helpful.
Excelente inversiĆ³n se la recomiendi
By ERICKSON FRANCISCO RODRIGUEZ
Es un programa muy completo me gusta mucho. Se lo recomiendo tanto para el diseƱo de investigaciĆ³n de mercados como para lo grĆ”ficos, tabulaciones ya lo he usado a travĆ©s de colegas profesores

See all 1 customer reviews...

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Uncertain Judgements: Eliciting Experts' Probabilities, by Anthony O'Hagan, Caitlin E. Buck, Alireza Daneshkhah, J. Richard Eiser, Paul H.

Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution. Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information. It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain Judgements introduces the area, before guiding the reader through the study of appropriate elicitation methods, illustrated by a variety of multi-disciplinary examples.

This is achieved by:

  • Presenting a methodological framework for the elicitation of expert knowledge incorporating findings from both statistical and psychological research.
  • Detailing techniques for the elicitation of a wide range of standard distributions, appropriate to the most common types of quantities.
  • Providing a comprehensive review of the available literature and pointing to the best practice methods and future research needs.
  • Using examples from many disciplines, including statistics, psychology, engineering and health sciences.
  • Including an extensive glossary of statistical and psychological terms.

An ideal source and guide for statisticians and psychologists with interests in expert judgement or practical applications of Bayesian analysis, Uncertain Judgements will also benefit decision-makers, risk analysts, engineers and researchers in the medical and social sciences.

  • Sales Rank: #2033388 in Books
  • Published on: 2006-09-01
  • Original language: English
  • Number of items: 1
  • Dimensions: 9.17" h x .96" w x 6.28" l, 1.34 pounds
  • Binding: Hardcover
  • 338 pages

Review

“This book, written by a group of expert statisticians and psychologists, provides an introduction to the subject and a detailed overview of the existing literature. The book guides the reader through the design of an elicitation method and details examples from a cross section of literature in the statistics, psychology, engineering and health sciences disciplines.”  (Zentralblatt Math, 1 August 2013)

"This is an interesting, well-written book that will be valuable to any decision maker who much rely on expert judgments, any statistician who uses Bayesian statistics, and any researcher who wishes to understand the field of elicitation." (Journal of the American Statistical Association, March 2009)

"This book provides an excellent introduction and working reference to the subject of its title and should be an invaluable aid to producers and consumers of expert opinion." (Biometrics, September 2008)

"I recommend 'Uncertain Judgements' as an excellent source for a wide variety of research." (Psychometrika, March 2008)

“…will be of interest to those who are concerned with or interested primarily in the practicalities of modeling expert judgement and opinion.” (International Journal of Marketing, January 2007)

From the Back Cover
Elicitation is the process of extracting expert knowledge about some unknown quantity or quantities, and formulating that information as a probability distribution.  Elicitation is important in situations, such as modelling the safety of nuclear installations or assessing the risk of terrorist attacks, where expert knowledge is essentially the only source of good information.  It also plays a major role in other contexts by augmenting scarce observational data, through the use of Bayesian statistical methods. However, elicitation is not a simple task, and practitioners need to be aware of a wide range of research findings in order to elicit expert judgements accurately and reliably. Uncertain Judgements introduces the area, before guiding the reader through the study of appropriate elicitation methods, illustrated by a variety of multi-disciplinary examples.

This is achieved by:

  • Presenting a methodological framework for the elicitation of expert knowledge incorporating findings from both statistical and psychological research.
  • Detailing techniques for the elicitation of a wide range of standard distributions, appropriate to the most common types of quantities.
  • Providing a comprehensive review of the available literature and pointing to the best practice methods and future research needs.
  • Using examples from many disciplines, including statistics, psychology, engineering and health sciences.
  • Including an extensive glossary of statistical and psychological terms.

An ideal source and guide for statisticians and psychologists with interests in expert judgement or practical applications of Bayesian analysis, Uncertain Judgements will also benefit decision-makers, risk analysts, engineers and researchers in the medical and social sciences.

About the Author
Professor Anthony O’Hagan is the Director of The Centre for Bayesian Statistics in Health Economics at the University of Sheffield. The Centre is a collaboration between the Department of Probability and Statistics and the School of Health and Related Research (ScHARR). The Department of Probability and Statistics is internationally respected for its research in Bayesian statistics, while ScHARR is one of the leading UK centres for economic evaluation.

Prof O’Hagan is an internationally leading expert in Bayesian Statistics.

Co-authors:

Professor Paul Gathwaite – Open University, Prof of Statistics, Maths and Computing

Dr Jeremy Oakley – Sheffield University

Professor John Brazier – Director of Health Economics Group, University of Sheffield

Dr Tim Rakow – University of Essex, Psychology Department

Dr Alireza Daneshkhah – University of Sheffield, Medical Statistics Department

Dr Jim Chilcott - School of Health Research, University of Sheffield, Department of OR

Most helpful customer reviews

3 of 3 people found the following review helpful.
Excellent Summary of an Important Topic
By Michael F. Cassidy
The book employs a comprehensive, multidisciplinary vantage to explore the important, and hoary, problem of eliciting probability judgments. It is effectively organized, well integrated, and offers practical advise that is grounded in sound theoretical and empirical work.

See all 1 customer reviews...

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Minggu, 15 September 2013

[C505.Ebook] Free PDF Big Data: Principles and best practices of scalable realtime data systems, by Nathan Marz, James Warren

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Big Data: Principles and best practices of scalable realtime data systems, by Nathan Marz, James Warren



Big Data: Principles and best practices of scalable realtime data systems, by Nathan Marz, James Warren

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Big Data: Principles and best practices of scalable realtime data systems, by Nathan Marz, James Warren

Summary

Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Book

Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive.

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful.

What's Inside

  • Introduction to big data systems
  • Real-time processing of web-scale data
  • Tools like Hadoop, Cassandra, and Storm
  • Extensions to traditional database skills

About the Authors

Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing.

Table of Contents

  • A new paradigm for Big Data
  • PART 1 BATCH LAYER
  • Data model for Big Data
  • Data model for Big Data: Illustration
  • Data storage on the batch layer
  • Data storage on the batch layer: Illustration
  • Batch layer
  • Batch layer: Illustration
  • An example batch layer: Architecture and algorithms
  • An example batch layer: Implementation
  • PART 2 SERVING LAYER
  • Serving layer
  • Serving layer: Illustration
  • PART 3 SPEED LAYER
  • Realtime views
  • Realtime views: Illustration
  • Queuing and stream processing
  • Queuing and stream processing: Illustration
  • Micro-batch stream processing
  • Micro-batch stream processing: Illustration
  • Lambda Architecture in depth
    • Sales Rank: #25989 in Books
    • Brand: Marz, Nathan/ Warren, James
    • Published on: 2015-05-10
    • Original language: English
    • Number of items: 1
    • Dimensions: 9.10" h x .60" w x 7.30" l, .0 pounds
    • Binding: Paperback
    • 328 pages

    About the Author

    Nathan Marz is currently working on a new startup. Previously, he was the lead engineer at BackType before being acquired by Twitter in 2011. At Twitter, he started the streaming compute team which provides and develops shared infrastructure to support many critical realtime applications throughout the company. Nathan is the creator of Cascalog and Storm, open-source projects which are relied upon by over 50 companies around the world, including Yahoo!, Twitter, Groupon, The Weather Channel, Taobao, and many more companies.

    James Warren is an analytics architect at Storm8 with a background in big data processing, machine learning and scientific computing.

    Most helpful customer reviews

    25 of 26 people found the following review helpful.
    Other books in this area tend to focus a lot more on the "gee whiz" coolness of data science and machine learning applications (
    By Kirk D. Borne
    I have rarely seen a thorough discussion of the importance of data modeling, data layers, data processing requirements analysis, and data architecture and storage implementation issues (along with other "traditional" database concepts) in the context of big data. This book delivers a refreshing comprehensive solution to that deficiency. Other books in this area tend to focus a lot more on the "gee whiz" coolness of data science and machine learning applications (which are aspects of big data that I happen to love, but they are not the whole story). You cannot hope to achieve good, effective, and efficient results from your analytics processes without good data flow, from discovery to access to integration, which is why architecture design, data modeling, and attention to data pipelining are essential. I highly recommend this book for anyone who isn't ashamed to admit that data engineering is at least as important as data science in the big data era (says this data scientist!).

    13 of 14 people found the following review helpful.
    A clear-eyed look at good ways to keep your Big Data system from becoming overwhelmed by complexity and volume
    By Si Dunn
    Here's my bottom line: Get this book, whether you are new to working with Big Data or now an old hand at dealing with Big Data’s seemingly never-ending (and steadily expanding) complexities.

    You may not agree with all that the authors offer or contend in this well-written "theory" text. But Nathan Marz’s Lambda Architecture is well worth serious consideration, especially if you are now trying to come up with more reliable and more efficient approaches to processing and mining Big Data. The writers' explanations of some of the power, problems, and possibilities of Big Data systems are among the clearest and best I have read.

    "More than 30,000 gigabytes of data are generated every second, and the rate of data creation is only accelerating," Marz and Warren point out.

    Thus, previous "solutions" for working with Big Data are now getting overwhelmed, not only by the sheer volume of information pouring in but by greater system complexities and failures of overworked hardware that now plague many outmoded systems.

    The authors have structured their book to show "how to approach building a solution to any Big Data problem. The principles you’ll learn hold true regardless of the tooling in the current landscape, and you can use these principles to rigorously choose what tools are appropriate for your application.” In other words, they write, you will “learn how to fish, not just how to use a particular fishing rod.”

    However, a particular Big Data architecture IS featured, as well: Marz's Lambda Architecture. It is, the two authors explain, "an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to Big Data systems that can be built and run by a small team."

    The Lambda Architecture has three layers: the batch layer, the serving layer, and the speed layer.

    Not surprisingly, the book likewise is divided into three parts, each focusing on one of the layers:

    In Part 1, chapters 4 through 9 deal with various aspects of the batch layer, such as building a batch layer from end to end and implementing an example batch layer.

    Part 2 has two chapters that zero in on the serving layer. "The serving layer consists of databases that index and serve the results of the batch layer," the writers explain. "Part 2 is short because databases that don’t require random writes are extraordinarily simple.”

    In Part 3, chapters 12 through 17 explore and explain the Lambda Architecture’s speed layer, which “compensates for the high latency of the batch layer to enable up-to-date results for queries.”

    Marz and Warren contend that "[t]he benefits of data systems built using the Lambda Architecture go beyond just scaling. Because your system will be able to handle much larger amounts of data, you’ll be able to collect even more data and get more value out of it. Increasing the amount and types of data you store will lead to more opportunities to mine your data, produce analytics, and build new applications."

    This book requires no previous experience with large-scale data analysis, nor with NoSQL tools. However, it helps to be somewhat familiar with traditional databases. Nathan Marz is the creator of Apache Storm and originator of the Lambda Architecture. James Warren is an analytics architect with a background in machine learning and scientific computing.

    (My thanks to Manning for providing a review copy of this book.)

    12 of 14 people found the following review helpful.
    Lambda Architecture FTW
    By Zambonilli
    Great explanation of both the theory and practice of the lambda architecture. While the practice chapters are nice, it's the theory chapters that really shine. The book explains down to the byte level why components are implemented the way they are. For example, there's an immense amount of detail as to why using a db that doesn't support random writes allows for an application to query the batch layer's results without locking.

    The only downside to the book is that the architecture and exosystem is so new that there's not really a lot of pragmatic solutions. For example, the theory describes a query layer that can merge the results of batch and real time processing for client applications. However, in real life there are no pragmatic solutions for doing this so you'd have to write your own.

    It'll be interesting to see how the lambda architecture matures and to see future editions of this book. Hopefully, future editions will be as well written and have a better ecosystem for practice chapters.

    See all 31 customer reviews...

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