A Data Science Central Community
In 2012, Harvard Business Review cited data scientist as the sexiest job of the 21st century. Just two months ago LinkedIn shared the “25 Hottest Skills that Got People Hired in 2014” – guess what type of workers possessed these skills? This attention has been followed with a slew of articles telling budding analysts the skills they’ll need to get to the top of the data scientist food…Continue
Added by Elana Roth on June 29, 2015 at 3:00am — No Comments
We all know that time is money, especially when you're paying a data scientist. But the New York Times reports that...
"Data scientists, according to interviews and expert estimates, spend 50 percent to 80 percent of their time mired in [the] mundane labor of collecting and preparing unruly digital data, before it can be explored for useful nuggets."…Continue
The comparison between MongoDB, the poster child of NoSQL, and MySQL has been raging for a while now. It is important that you know the difference between the two as this will assist you in making an informed decision.
The Major Differences between MongoDB and MySQL
1. There is a difference in the representation of data in the two databases. In…Continue
I have built a model that scores 99.9% accuracy! Great! Fantastic!
This is what a colleague of mine calls the "Now what?" effect. After training, testing, and optimizing a model repeatedly, we get this fantastic performance on the evaluation set. Now it is the time to put your model to good use on real life, maybe streaming, data. This phase is called Model…
Added by Rosaria Silipo on June 23, 2015 at 1:28am — No Comments
Business intelligence solutions have come a long way in the past five years with continued innovation and transformation from traditional BI to data visualization and data discovery. With the advent of improved BI tools and accessibility, many businesses are using precious IT budgets to add self-serve business intelligence to their solution infrastructure and put the power of self-serve BI tools into the hands of their employees and business users.
Vendors like …Continue
Added by Kartik Patel on June 23, 2015 at 12:00am — No Comments
A/B testing is widely used for online marketing, management of Internet ads or any other usual analytics. In general, people use it in order to look for "golden features (metrics)" that are vital points for growth hacking. To validate A/B testing, statistical hypothesis tests such as t-test are used and people are trying to find any metric with a significant effect across conditions. If you successfully find a metric with a significant difference between design A and B of a click button,…Continue
Added by Takashi J. OZAKI on June 18, 2015 at 9:00am — No Comments
If you’re relatively new to the Natural Language Processing and Text Mining world, you’ll more than likely have come across some pretty technical terms and acronyms, that are challenging to get your head around, especially, if you’re relying on scientific definitions for a plain and simple explanation.
We decided to put together a list of 10 common terms in Natural Language Processing which we’ve broken down in layman terms, making them easier to understand. So if you don’t know your…Continue
Added by Mike Waldron on June 17, 2015 at 4:38am — No Comments
I would like to bring to your attention my book of 1998 on my beliefs-preferences gauge symmetry that might be of interest to you:
 V.A. Kholodnyi, Beliefs-Preferences Gauge Symmetry Group and Replication of Contingent Claims in a General Market Environment, IES Press, Research Triangle Park, North Carolina, 1998.
I introduced the beliefs-preferences gauge symmetry as well as the related differential-geometrical and…Continue
Added by Valery A. Kholodnyi on June 11, 2015 at 2:00am — No Comments
Good Morning and Welcome to this edition of the Morning Analytic Coffee Blog.
Today, we talk about the understanding of project parameters, and being eager to please. One of the best and worst things for the analyst is project parameters: Written clearly, with a good understanding, project parameters can really help provide the structure for the results needed. Notice that I didn’t say “results desired…Continue
Added by Richard D. Quodomine on June 9, 2015 at 10:30am — No Comments
In my own blog I wrote a series of articles about how major machine learning classifiers work, with some visualization of their decision boundaries on various datasets.
Added by Takashi J. OZAKI on June 5, 2015 at 4:00am — No Comments
Fraud detection is all about connecting the dots. We are going to see how to use graph analysis to identify stolen credit cards and fake identities. For the purpose of this article we have worked with Ralf Becher, irregular.bi. Ralf is Qlik Luminary and he provides solutions to integrate the Graph approach into Business Intelligence solutions like QlikView and Qlik Sense.
Third party fraud occurs when a…Continue