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December 2015 Blog Posts (116)

Tons of machine learning and data science resources that cost nothing

Tutorials, books, articles, data sets, certifications, you name it. All about data science, machine learning and related topics. You can find them with a simple keyword search: enter the keyword "free" in the DSC's search box, and here are the results.

Below is a screenshot of the DSC search results page, for the keyword "free".…

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Added by L.V. on December 3, 2015 at 11:30am — 1 Comment

Just When You Thought You Understood RDBMS and NoSQL Databases – This Happens

Summary:  Just when you thought you had a handle on the database market it fragments again.  Here’s an overview to help you keep up.…

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Added by William Vorhies on December 3, 2015 at 9:30am — No Comments

Essentials of R: An NFL Example

Learning any new skill is hard. There are too many possibilities, and the goal seems massive and intimidating.

Enter the Pareto Principle.

The Pareto Principle, also known as the 80/20 rule, suggests that 80 percent of results come from 20 percent of efforts. It can be applied to everything from business to language, even learning how to use R.

With just a…

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Added by Divya Parmar on December 3, 2015 at 8:42am — No Comments

Great Data Science and Machine Learning Podcasts

This was a question recently posted on Quora: What are the best data science podcasts?. Users recommend the following ones:

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Added by L.V. on December 2, 2015 at 5:00pm — No Comments

10 Big Data Use Cases Everyone Must Read

What do you think of when you think of "big data"?

For many, it's a nebulous term that invokes images of huge server farms humming away. Or perhaps you think of receiving some kind of personalized advertisement from a retailer.

But big data is so much deeper and broader than that. I believe there are 10 major areas in which big data is currently being used to excellent advantage in practice - but within those arenas,…

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Added by Bernard Marr on December 2, 2015 at 3:30pm — 2 Comments

Meaning and purpose of Business Intelligence - Did we lose the true purpose somewhere?

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  Companies in a variety of industries are still data-rich but information-poor and this ratio keeps increasing every day. The rate of data generation is so high that organizations simply cannot keep up with generating insights out of it.

These enterprises lack the kind of actionable information and analytical tools needed to improve profits and performance. Business intelligence (BI) is the…

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Added by Nilesh Jethwa on December 2, 2015 at 11:00am — No Comments

Weekly Digest, December 7

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has 6 sections: (1) Featured Articles and Case Studies, (2) Featured Resources and Technical Contributions, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.

The full version is always published Monday.…

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Added by Vincent Granville on December 2, 2015 at 10:00am — No Comments

6 Often Forgotten ROI Factors In Data Analytics







Big…

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Added by David Lefkowich on December 2, 2015 at 8:30am — 1 Comment

100 Data Science Interview Questions and Answers

This article is no longer available. We apologize for the inconvenience. To read more about data science interview questions, click here. We highly recommended the following reading:…

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Added by William Vorhies on December 2, 2015 at 8:00am — 3 Comments

The Collective Definition of Data Lake by Big Data Community

Yes, we are marching towards New Year 2016!  What happened to Resolution of 2014, 2015? Quit Habits? Practice Habits? Road ahead? Am into all, but i could not able to keep it up. Hence this New Year 2016 is no more resolutions, just implement the plan.

Extend to that, as we know big data is bringing more business value to enterprise by leveraging the data lake. Data Lake..... What is that? Data Lake is loosely defined word and the definition gets changed during implementation…

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Added by Kumar Chinnakali on December 2, 2015 at 5:00am — No Comments

The Data-Driven Weekly #1.4

With the holiday shopping season officially kicked off, sales data is on everyone's mind. But that's not the only data people are talking about. Talk of data brokers and consumer tracking is becoming more commonplace, as is a certain backlash against big data. This week, we highlight some articles touching on these subjects and round out the discussing with some coverage of natural language processing techniques.





Data Brokers

Everyone knows about online…

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Added by Brian Rowe on December 1, 2015 at 1:01pm — No Comments

3 Tips for Centralizing Your Analytics Team Structure As You Grow

Nearly a year ago we wrote about the questions folks should consider when making early analytics hires. While those questions are helpful whether you’re hiring your first data analyst or your fourth, there will be undoubtedly be another nagging question as you scale:…

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Added by Melissa Bierly on December 1, 2015 at 11:30am — No Comments

3 Reasons why analytics projects are falling short - and what we can do about it

Guest blog by Nidhi Arggarwal of Tamr

 

A recent Forbes Insight/Teradata survey of 316 large global company executives found that 47% “do not think that their companies’ big data and analytics capabilities are above par or best of breed.” Given that “90% of organizations report medium to high levels of investment in big data analytics,” the executives’ self-criticism begs the question:…

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Added by Jason Bailey on December 1, 2015 at 7:30am — No Comments

What you won't learn in stats classes

There are many topics that you won't learn in statistics classes. Some such as U-Statistics, stochastic geometry, fractal compression, and stochastic differential equations, are for post-graduate people. So it is OK to not find them in statistics curricula. Others like computational complexity and L^1 metrics (to replace R-squared and other outlier-sensitive L^2 metrics such as traditional variance) should be included, in my opinion.

But the classic statistics curriculum is almost…

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Added by Vincent Granville on December 1, 2015 at 7:00am — No Comments

How to Build Data Science Teams

Prior this month Impact Team individuals Madalin Mihailescu and Chris Matys facilitated a talk with our portfolio organization CTOs on the point of employing and scaling up information science groups. Here are some brisk flame takeaways from that exchange:

1 Hire Teams, Not Unicorns

We regularly hear that the information researcher is a unicorn. They are not unless you are attempting to contract one who can do it all: Product Manager, Data Scientist,…

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Added by Jay Rocket on December 1, 2015 at 12:30am — 1 Comment

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