This topic combines two of the most difficult or least understood ML techniques and challenges.  Fraud detection invariably falls short of complete automatic detection because of the false positive rate and the need for at least some human intervention, typically on a case-by-case basis.  Deep Learning, one of the most far flung borders of ML research utilizing neural net architecture but unsupervised model development.

Our friends at H2O University…

Guest blog from David Lefkowich

Almost every notable project we’ve completed with our clients over the past 3 years has had one major factor in common. Each originated from a complicated spreadsheet-driven data manipulation and reporting process that the company had outgrown. The corporate business needs evolved or expanded. Perhaps a new regulation or requirement came into effect, or an acquisition took place and new data needed to be integrated into the reporting process.…

Guest blog by Tomislav Bacingeris @ Toptal

Data Driven Documents, or…

Summary:  Stream Processing and In-Stream Analytics are two rapidly emerging and widely misunderstood data science technologies.  In this article we’ll focus on their basic characteristics and some business cases where they are useful.

There are five relatively new technologies in data science…

Guest blog by Alleli Aspili at Infinit Datum

Big data became more than a buzzword when industries discovered its huge potential. And with this finding, came a new science called data analytics.

The demand to understand all the…

Guest blog by…

XKCD.com

If you’re fortunate enough to have a quantitative PhD, you may have thought about applying for an opening in data science.  After all, it’s an exciting and well paid field and a lot of…

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 Guest blog by Greg Roberts at Packt Publishing

(to see this graph in its fully interactive form see http://gregroberts.github.io/)

I love Python, and to celebrate…

Summary:  Over 80% of companies are not yet using advanced analytics.  Here’s a step-by-step plan to implement a brand new predictive analytics program getting the biggest bang for your buck from the most cost effective investment.  Part 2.

In Part 1…

Guest blog by David…

This article is no longer available. We apologize for the inconvenience. To read more about data science and game theory, click here. 

Summary:  Over 80% of companies are not yet using advanced analytics.  Here’s a step-by-step plan to implement a brand new predictive analytics program getting the biggest bang for your buck from the most cost effective investment.

Are You (Your Company) Part of the 80% or the 20%?…