Sabtu, 14 Agustus 2010

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Product details

File Size: 6153 KB

Print Length: 424 pages

Simultaneous Device Usage: Up to 2 simultaneous devices, per publisher limits

Publisher: Pearson; 10 edition (March 14, 2011)

Publication Date: March 14, 2011

Sold by: Amazon Digital Services LLC

Language: English

ASIN: B008UFWZ9Q

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Amazon Best Sellers Rank:

#144,890 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

I bought this book for a class and ended up with two books and was charged for two books, with both books being mailed separately. When I emailed the company about the issue they will charge me a 15% restock fee. I have had difficulty following along with my assignments because it appeared that some of the chapters were missing and when I turned the book over this was printed on the back of the book: "This is a special adaptation of an established title widely used by colleges and universities throughout the world. Pearson published this exclusive edition only for the benefit of students outside the United States and Canada. If you purchased this book within the United States or Canada you should be aware that it has been imported without the approval or permission of the Publisher or the Author" I recommend not buying this book from RMillestexts

I bought this book for an online Public School Law class and it took almost 10 days to arrive at my house. I quickly realized that this book had missing chapters and on the back of the book this is printed: "This is a special adaptation of an established title widely used by colleges and universities throughout the world. Pearson published this exclusive edition only for the benefit of students outside the United States and Canada. If you purchased this book within the United States or Canada you should be aware that it has been imported without the approval or permission of the Publisher or the Author" I recommend not buying this book from RMillestexts. They also charge a 10% restocking fee, even though it was misrepresented in the online description. Very disappointing.

Good resource for my educational law class. The author has done a good job of keeping the case analyses succinct and understandable, makes them accessible for the lay person who needs to understands precedents to our current laws.

I had to purchase this book for a School Law class I was taking for my graduate degree. Although we were only required to read a certain chapter to present, I found myself reading more than the required- especially after hearing presentations each week. This book gives snid-bits of court cases for various categories.. it definitely explains why some things are the way they are in schools. Most the cases are from pretty old, so my one critique is that I wish it had more recent cases since education has changed so much over time.

school book

I do not like the Kindle version of this book. This is my first time using a text book in Kindle format and will be my last!!! E-books have been great for me, but I am not able to scroll through pages easily and navigate. Very disappointed.

Required for school law class. Interesting to read but at times difficult to understand. If I was a law student I would have probably been more familiar with the jargon and understood it, but being in education, it would have been helpful to have been written with the audience of the teacher in mind. I had to look up some cases just to find out the outcome of the case since it wasn't written in such a way that seemed obvious.

It's a textbook that you get assigned to read for class, so you probably aren't ordering it for pleasurable reading. Having said that, the book is very well written, easy to read, and understand. I found it very informative.

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Jumat, 06 Agustus 2010

Free Ebook Social Media Data Mining and Analytics

Free Ebook Social Media Data Mining and Analytics

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Social Media Data Mining and Analytics

Social Media Data Mining and Analytics


Social Media Data Mining and Analytics


Free Ebook Social Media Data Mining and Analytics

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Social Media Data Mining and Analytics

From the Back Cover

LEARN TO MINE SOCIAL MEDIA DATA FOR A COMPETITIVE EDGE Social media is a rich source of big data, so much so that 90% of Fortune 500 companies are investing in big data initiatives to help them predict consumer behavior. Knowing the most effective ways to mine social media data can help you acquire information that generates amazing business results. Social media is unstructured, dynamic, and future-oriented. Effective, insightful data mining requires new analytical tools and techniques. Written by experts at social networking companies, Social Media Data Mining and Analytics provides a hands-on course that teaches you how to use state-of-the-art tools and sophisticated data mining techniques specifically geared to social media. It digs deeply into the mechanics of collecting and applying social media data to understand customers, define trends, and make predictions that can improve analytics for growth and sales. You will discover how to make the most of data gathered from social media and other related rich data sources. You'll learn how to identify common patterns of online user behavior so you can independently build and apply predictive algorithms that exploit these patterns. Social Media Data Mining and Analytics will teach you: The four key characteristics of online services: users, social networks, actions, and content The data discovery lifecycle: data extraction, analysis, and visualization Techniques for using social media to make customer predictions and recommendations How to use distributed computing to efficiently process large amounts of social media data Solutions using code-level examples written in Python, R, and Scala

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About the Author

GABOR SZABO, PHD, is a Senior Staff Software Engineer at Tesla and a former data scientist at Twitter, where he focused on predicting user behavior and content popularity in crowdsourced online services, and on modeling large-scale content dynamics. He also authored the PyCascading data processing library. GUNGOR POLATKAN, PHD, is a Tech Lead/Engineering Manager designing and implementing end-to-end machine learning and artificial intelligence offline/online pipelines for the LinkedIn Learning relevance backend. He was previously a machine learning scientist at Twitter, where he worked on topics such as ad targeting and user modeling. P. OSCAR BOYKIN, PHD, is a software engineer at Stripe where he works on machine learning infrastructure. He was previously a Senior Staff Engineer at Twitter, where he worked on data infrastructure problems. He is coauthor of the Scala big-data libraries Algebird, Scalding and Summingbird. ANTONIOS CHALKIOPOULOS, MSC, is a Distributed Systems Specialist. A system engineer who has delivered fast/big data projects in media, betting, and finance, he is now leading the effort on the Lenses platform for data streaming as a co-founder and CEO at https://lenses.stream.

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Product details

Paperback: 352 pages

Publisher: Wiley; 1 edition (October 23, 2018)

Language: English

ISBN-10: 1118824857

ISBN-13: 978-1118824856

Product Dimensions:

7.4 x 0.8 x 9.1 inches

Shipping Weight: 1 pounds (View shipping rates and policies)

Average Customer Review:

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Amazon Best Sellers Rank:

#929,302 in Books (See Top 100 in Books)

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