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Patrick Bulteel

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Interesting read...
Hello everyone, This is Tugce from Victoria University Melbourne Australia. Me and my team mate Luke did some researches on domestic violence and prepared some visualizations in SAP Lumira for anal...
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The concept of the data lake is growing in popularity in the big data world and so are the counts of warnings about your data lake becoming a data swamp, a data marsh or a data cesspool. 
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astrid ayel's profile photoIsabelle Ayel's profile photo
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In this post, I'll explore the new AWS Machine Learning services.
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JeevaN E L's profile photoDavid Esposito's profile photo
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Yuriy Chesnokov

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There's been an explosion of interest in Bayesian statistics. John Kruschke discusses new computational methods that have made data analysis accessible.
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Ivan Kuznetsov

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Jose David Posada Aguilar's profile photoTrevor Ewart's profile photoBecky Lambert's profile photomgalka's profile photo
 
Looks like not about skills list, rather courses list.
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Here is a list of top Python Machine learning projects on GitHub.
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Amir habibdoust's profile photoPhilip Marais's profile photo
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mina rahimi

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Google issues an apology for insulting Maps mess up

Post by +Jimmy Westenberg 
Google Maps has been experiencing a ton of issues lately. A couple of weeks ago, a 'clever' Google Maps user submitted an image of the Android mascot peeing on an Apple logo, which forced Google to shut down editing in the Map Maker program to ensure it wouldn't happen again. The Google Maps team apologized for the incident, and we all moved on. Then just a few days ago, users discovered that typing an offensive term into Maps would bring you str...
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Guido Stepken

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Big data and weather forecast. A billion dollar business.


Imagine tomorrow there would be no weather!?? 
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Ritesh Sanghani

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How data entry can help companies to establish a quick and secure database? Learn more at http://goo.gl/3hxyBO
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I asked myself this question a few months ago. Next I thought: What is the definition of Data Science? So the first thing I started to do is read as many posts on the topic as I could get my hands on and also lookup definitions of related topics such as Data Mining and Machine Learning. Looking at the discussions and posts around Data Science it seems to span everything needed to understand data, to derive something out of data and communicate the finding. This does not really help to answer the original question, so let´s take a closer look.
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Very interesting!
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It's a home for anybody data-curious, whether your data is big, small, square or scruffy. If you think you can decide better, do better, or be better through data, you belong here! Before posting, please check out our guidelines below.
 
We've published such articles in the past.  Here are recent reports from external sources. The first one below comes from FollowerWonk.com. You can choose a topic, to find top influential people related to the topic in question. Below is their selection as of May 28, 2015, for the keyword 'big data'. We also tried 'data science', but the results had a glitch: the #1 was irrelevant; it had the keywords 'data' and 'science' separately in the entry, but not 'data science'. It is amazing to see that scoring systems relying on NLP (natural language processing) algorithms still have such terrible, easy-to-fix glitches in 2015. These scoring algorithms do not use sound data science to (automatically) produce the lists. 
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Nikki Bednall's profile photoDavid Esposito's profile photo
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This is part of our series about how programming languages and platforms used to deliver successful data science nuggets. Our previous articles were about Python and Excel. Our upcoming articles will be about SAS, SQL,Tableau, NoSQL, Teradata, Hadoop and many more.
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Jen Yoeng's profile photoKen Bury's profile photoLudovic Carceles's profile photo
 
Thank you very much for sharing this article! It's very interesting
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Yuriy Chesnokov

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Today, I’m going to explain in plain English the top 10 most influential data mining algorithms as voted on by 3 separate panels in this 2007 survey paper.
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Mahendranath Reddy's profile photo宋云生's profile photoJesus M. Castagnetto's profile photoWilliam Hey Tow's profile photo
 
Could you combine a grouping algorithm like k means and a decision tree to classify new data without having to manually label the training data ? Or is that relying too much on a potentially erroneous result from k means?
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I've never met a word cloud that didn't make me wonder "why am I even looking at this"? Image is from the Machine Learning Group at University of
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There are actually dozens if not hundreds of articles about Excel (for data science) on DSC, and a quick way to find them (or articles on any topic such as R) is to use our search box. Our search box is powered by Google, but it returns results from selected websites only, making search results much more relevant to DSC visitors. A popular article is about how to make maps with Excel. In our cheat sheet and upcoming book Data Science 2.0, many of our new data science techniques - easier to implement than traditional statistical models, yet more powerful - are also illustrated using Excel. An example is Jackknife regression with Excel.
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Trevor Ewart's profile photoMatthew Green's profile photo
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Buzz words are one of my least favorite things, but as buzz words go, I can appreciate the term “Data Lake.” It is one of the few buzz words that communicates a meaning very close to its intended definition. As you might imagine, with the advent of large scale data processing, there would be a need to name the location where lots of data resides, ergo, data lake. I personally prefer to call it a series of redundant commodity servers with Direct-Attached Storage, or hyperscale computing with large storage capacity, but I see the need for a shorter name. Also, the person that first coined the phrase could just have easily called it Data Ocean, but they were modest and settled for Data Lake. I like that.
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Edward Meinert

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#bigdata  Myth Busting
In this video, Yusuf Ermak addresses some big data myths.  To learn more about Yusuf and his insights, register for Big Data for Health.
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Python & data analytics go hand in hand. Here is a list of 9 Python data analytics libraries. This list is going to be continuously updated here.
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prasad k

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Registering for this site is easy. Just fill in the fields below, and we'll get a new account set up for you in no time. Account Details. Username (required) Email Address (required) Choose a Password (required). Confirm Password (required). Profile Details. Name (required) ...
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This is an interesting article recently published in Forbes. The author gathered data from Glassdoor.com, to rank companies. Glassdoor.com is a website where employees make comments about, and rate their company, and can even post their job title and salary range. Keep in mind that the author is not a statistician, and his analysis is based on user-generated content, which, like all reviews, can be fake. Yet the author removed companies with less than 10 reviews, to make this table more robust. So if your start-up is not listed, it's not because it's not in the top, but because there are too few ratings to make a sound conclusion about it.
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