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• Sales Rank: #3906694 in Books
• Brand: Brand: Cengage Learning
• Published on: 2007-12-13
• Original language: English
• Number of items: 1
• Dimensions: 1.45" h x 7.34" w x 9.13" l, 2.66 pounds
• Binding: Paperback
• 712 pages

Features

• Used Book in Good Condition

Review
1. Overview of Planning a Windows Server 2003 Network 2. TCP/IP Architecture 3. Planning Network Data Flow 4. Planning and Configuring Routing and Switching 5. Planning, Configuring, and Troubleshooting DHCP 6. Planning, Configuring, and Troubleshooting WINS 7. Planning a DNS Strategy 8. Managing and Troubleshooting DNS 9. Planning and Managing Certificate Services 10. Planning and Managing IP Security 11. Planning Network Access 12. Planning and Implementing Server Availability and Scalability 13. Planning Server and Network Security 14. Problem Recovery Appendices A: Exam Objectives Tracking for MCSE Certification Exam #70-293 B: Detailed Lab Setup Guide C: Expanded Chapter Summaries New Tear-Out Practice Exam

About the Author
Byron Wright is a Partner in Conexion Networks, a computer consulting firm that implements and maintains networks, e-mail systems, and security for a wide variety of organizations. In addition to possessing a Bachelor of Commerce degree (B. Comm), Wright is a Microsoft Certified Trainer (MCT), a Certified Novell Instructor (CNI), Microsoft Certified Systems Engineer (MCSE), a Certified Novell Engineer (CNE), and Certified Linux Professional (CLP). Wright also is a sessional instructor with the University of Manitoba teaching Information Systems for the Asper School of Business. As well, Byron has authored and co-authored a number of books for Cengage - Course Technology, including MCSE Guide to Microsoft Windows Vista, MCSE Guide to Microsoft Exchange Server 2003 Administration, and MCSE Guide to Planning a Microsoft Windows Server 2003 Network.

Dr. Brian T. McCann has taught courses in managerial economics, strategic management, and entrepreneurship at the undergraduate, MBA and executive education levels. He holds an MBA from Vanderbilt University where he earned the Founder's Medal as the top graduate of the class. Dr. McCann received his doctoral training in strategic management at Purdue University's Krannert School of Management where he was awarded the Ross Fellowship, the Krannert Certificate for Distinguished Teaching, and the Purdue Research Foundation Research Grant. His more than 10 years of industry experience include operating a residential land development company, serving as the CFO for an Internet start-up, and implementing new strategic initiatives for a non-profit economic development group. In addition to co-authoring this MBA-level textbook in managerial economics, Dr. McCann's work has appeared or is forthcoming in journals, such as STRATEGIC MANAGEMENT JOURNAL, JOURNAL OF MANAGEMENT, and JOURNAL OF MANAGEMENT STUDIES. His current research interests span strategic management and entrepreneurship and include the performance implications of firm agglomeration, the effects of ownership structure on competitive behaviors, and the role of threshold-based decision making in the entrepreneurial process.

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0 of 0 people found the following review helpful.
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FEATURES:

• Provides an introduction to programming interactive computer graphics, with an emphasis on game development using DirectX 12

• Uses new Direct3D 12 features to reduce CPU overhead and take advantage of multiple CPU cores

• Contains detailed explanations of popular real-time game effects

• Includes a DVD with source code and all the images (including 4-color) from the book

• Learn advance rendering techniques such as ambient occlusion, real-time reflections, normal and displacement mapping, shadow rendering, programming the geometry shader, and character animation

• Covers a mathematics review and 3D rendering fundamentals such as lighting, texturing, blending and stenciling

• Use the end-of-chapter exercises to test understanding and provide experience with DirectX 12

• Sales Rank: #183845 in Books
• Published on: 2016-03-24
• Original language: English
• Number of items: 1
• Dimensions: 9.00" h x 1.60" w x 7.00" l, .0 pounds
• Binding: Paperback
• 900 pages

About the Author
Frank Luna has been programming interactive 3D graphics with DirectX for more than fifteen years. He is the author of three bestselling books on DirectX and has worked in 3D medical visualization, 3D architectural design software, and gaming. He holds a BS in mathematics from the University of California, Irvine.

Most helpful customer reviews

14 of 15 people found the following review helpful.
Absolutely no effort was put into this book. It's ...
By Amazon Customer
Absolutely no effort was put into this book. It's a copy paste of the previous book on DirectX 11. In several chapters, the author didn't event bother changing "Direct3D 11" to "Direct3D 12", so it creates a very confusing mess.

8 of 10 people found the following review helpful.
Good, but missing some things
By Amazon Customer
I haven't read the entire thing but so far it's pretty good.

But just so people know, the chapters on terrain rendering and particle systems that were in the d3d11 book are gone.
And the book doesn't teach you "how to take advantage of multiple cores." as it states on the back, the book directs you to look at microsoft samples.

One cool thing though is the lighting model you implement is a bit more advanced than the one in the d3d11 book.

1 of 1 people found the following review helpful.
more like introduction to directx12 with 3d game programming
By francis
more like introduction to directx12 with 3d game programming. it has everything I need to get started programming graphics and as a begginner I can only get better with this book.

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Excerpt:

You may have seen them. Maybe you are one of them. The teens who prefer to be alone and who avoid making social connections with their peers. The adult who stays in his basement playing videogames or browsing the Internet. The little boy who chases frogs at the pond by himself instead of finding some friends to go fishing with. Maybe it is the woman who surrounds herself with cats and lives deep in the country, rarely venturing into town - even for necessities. Are these people shy, or do they have something that is much more pervasive?

Humans, by nature, generally want to be social with others. We thrive on conversation, interaction, and learning from each other. We were designed to be able to pass along our knowledge to the generations that come after us, and we strive to educate ourselves in order to be more sufficient and able to provide for our families or become productive members of society.

There is a subset of people who are different from the normal population. Their brains are wired a bit differently, or they went through experiences in their lives that contributed to their introversion, social avoidance, and shyness. They may have been sensitive children who were neglected or abused, never encouraged to learn about the world around them. Their feelings may have been invalidated while they were young, so they learned to keep their emotions inside instead of sharing them with others around them. They learned to be self-sufficient instead of relying on others and on society for their needs.

Some of these shy individuals who we classify as loners may be afflicted with a disorder called schizoid personality disorder...."

From four-time best-selling author J. B. Snow.

• Sales Rank: #109288 in Audible
• Published on: 2015-07-02
• Format: Unabridged
• Original language: English
• Running time: 30 minutes

Most helpful customer reviews

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You're done before you even knew you'd started
By Amazon Customer
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• Sales Rank: #4526981 in Books
• Brand: Brand: Quadrangle/New York Times Book Co
• Published on: 1975
• Number of items: 1
• Binding: Unbound
• 181 pages

Features

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Hockey Puzzlers: Offbeat Trivia for the Fan and the Fanatic, by Bob Moll

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Hockey Puzzlers contains over 100 hockey trivia questions spanning seven categories. Questions include offbeat rules and game history that will entertain both fans and fanatics.

• Sales Rank: #18810 in Books
• Published on: 2015-11-25
• Dimensions: 8.00" h x .18" w x 5.25" l,
• Binding: Paperback
• 76 pages

About the Author
Bob Moll is an author, product designer and avid hockey fan.

Most helpful customer reviews

2 of 2 people found the following review helpful.
a fun hockey gift
By loey
my daughter is a big hockey fan, so this was a fun little gift to give her

2 of 2 people found the following review helpful.
Five Stars
By Barbara K.
Clever and enjoyable for hockey lovers.

2 of 2 people found the following review helpful.
Five Stars
By Gene Koerner
Keeps the kids busy and they love it.

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• Published on: 2004-10-04
• Binding: Unknown Binding

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Leverage the power of Scala with different tools to build scalable, robust data science applications

About This Book

• A complete guide for scalable data science solutions, from data ingestion to data visualization
• Deploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizations
• Build functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples provided

Who This Book Is For

If you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions.

What You Will Learn

• Transform and filter tabular data to extract features for machine learning
• Implement your own algorithms or take advantage of MLLib's extensive suite of models to build distributed machine learning pipelines
• Read, transform, and write data to both SQL and NoSQL databases in a functional manner
• Write robust routines to query web APIs
• Read data from web APIs such as the GitHub or Twitter API
• Use Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirements
• Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations
• Deploy scalable parallel applications using Apache Spark, loading data from HDFS or Hive

In Detail

Scala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and scripting language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines.

This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala.

Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala's emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks.

This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.

Style and approach

A tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

• Sales Rank: #866758 in Books
• Published on: 2016-01-28
• Released on: 2016-01-28
• Original language: English
• Number of items: 1
• Dimensions: 9.25" h x .94" w x 7.50" l, 1.57 pounds
• Binding: Paperback
• 416 pages

About the Author

Pascal Bugnion

Pascal Bugnion is a data engineer at the ASI, a consultancy offering bespoke data science services. Previously, he was the head of data engineering at SCL Elections. He holds a PhD in computational physics from Cambridge University. Besides Scala, Pascal is a keen Python developer. He has contributed to NumPy, matplotlib and IPython. He also maintains scikit-monaco, an open source library for Monte Carlo integration. He currently lives in London, UK.

Most helpful customer reviews

4 of 4 people found the following review helpful.
A practical approach to taming data science with Scala's functional paradigm
By adnan baloch
One of the hottest jobs these days is that of the data scientist. It makes sense given the explosion of data generated by the online activities of millions of internet users and collected by online businesses and social media websites. As the author of this book explains, data scientists need to be conversant in three areas at once: programming, statistics/numerical algorithms and the ability to ask the right questions that will help in making decisions crucial to expanding a business and keeping it competitive. This book deals with the first of these essential skills: programming. Scala is a functional programming language with powerful parallel computing capabilities. The functional part of the language ensures that code written in Scala is terse and avoids common bugs that are the major source of headaches in traditional languages like Python or Java. The one place where Scala lags is in the availability of mature libraries. Still, the author discusses several good Scala libraries that make the Scala programmer's job easy so she can focus on the actual data science. Breeze and Breeze-viz are put to use in manipulating arrays of data and plotting simple graphs respectively. Parallel collections are explained intuitively so that anyone without any experience of parallel computation will find it useful. Futures make it possible to add further concurrency to Scala based projects by freeing the main thread from blocking events like waiting to receive data from a web page.
Databases form the core of data storage in any data focused programming solution. The author shows how to write a functional wrapper for JDBC and also discusses a popular functional wrapper called Slick so the readers will be equipped to handle both scenarios depending on their needs. Gathering data from the web can hardly work without an understanding of interfacing with APIs. The author takes a very practical approach in exploring this crucial aspect by querying the Github API and storing the data in MongoDB. Furthermore, readers get to see how to create their own simple web API. Sooner or later, data scientists have to turn to distributed computing for the horsepower needed to complete their complex calculations. Actor based concurrency using Akka fills this gap and the author gives it an excellent treatment in a dedicated chapter. Machine learning is discussed using MLlib but a good conceptual understanding of ML is needed for this chapter. The uninitiated are forewarned: don't expect the author to teach machine learning in a single chapter. For me, the most exciting two chapters are the ones that use the Play framework with D3.js to build a single page app. This represents true empowerment because it enables budding data scientists to share their fruits of labor with the entire web community in a visually captivating way. In short, data scientists wondering about Scala's effectiveness as a great tool for data science need only skim through this book. They won't be disappointed.

3 of 3 people found the following review helpful.
Scala for Data Science was a fairly good introduction for me to applied Scala applications and interoperability
By DWR
Scala for Data Science was a fairly good introduction for me to applied Scala applications and interoperability. Working through a few examples in this book proved to be my first foray into using Scala. In my opinion, the book seemed a bit light on techniques for statistical learning, but was rich in tools showing how to Scala with JSON, APIs, SQL, MongoDB, and Spark.

2 of 2 people found the following review helpful.
Great book!
By Timothy J. Whittaker
I spent a lot of time looking for a book like this. The other reviewer is correct, there is very little on actual statistical learning in this text, but this is not the author's aim. To me, this is more about awareness of some great Scala (and Java) libraries (with application) that any data scientist should find useful. The definition of data science taken by this book is probably the broadest I have seen - there is something worthwhile in every single chapter of this book.

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