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August 2017 Blog Posts (14)

Overpromising and Underperforming: Understanding and Evaluating Self-service BI Tools

From the OLAP concept in earlier years to the agile BI over the last few years, BI vendors never stop advertising the self-service capability, claiming that business users will be able to perform analytics by themselves. Since there are strong self-service needs among users, the two really hit it off and it is very likely that a quick deal is made. The question is - does a BI product’s self-service functionality enable a truly flexible data analytics by business users?

There isn’t a…


Added by JIANG Buxing on August 31, 2017 at 12:00am — 1 Comment

Python Overtakes R for Data Science and Machine Learning

This article summarizes a trend in programming languages usage, based on a number of proxy metrics. This change started to be more pronounced in early 2017: Python became the language of choice, over R, for data science and machine learning applications. 

Some statistics

We have 83 fresh, active job ads, relevant to data science and mostly in US and London, for Python: …


Added by Vincent Granville on August 30, 2017 at 7:30pm — No Comments

Great Sunday Reading

The following articles and resources were featured today:


Added by Vincent Granville on August 27, 2017 at 12:10pm — No Comments

The Fundamentals of Data Science

Guest blog post by Mic Farris. Mic is a Decision Science & Analytics Leader at CenturyLink.

Two of the biggest buzzwords in our industry are “big data” and “data science”. Big Data seems to have a lot of interest right now, but Data Science is fast becoming a very hot topic.

I think there’s room to really define…


Added by Vincent Granville on August 24, 2017 at 5:30pm — No Comments

Understanding Basic Reinforcement Learning Models

Summary:  Reinforcement Learning (RL) is likely to be the next big push in artificial intelligence.  It’s the core technique for robotics, smart IoT, game play, and many other emerging areas.  But the concept of modeling in RL is very different from our statistical techniques and deep learning.  In this two part series we’ll take a look at the basics of RL models, how they’re built and used.  In the next part, we’ll address some of the complexities that make development a…


Added by Vincent Granville on August 23, 2017 at 2:30pm — No Comments

Great Friday Reading

Here is our list of newly featured articles and resources:


Added by Vincent Granville on August 18, 2017 at 8:50pm — No Comments

Curious Mathematical Object: Hyperlogarithms

Logarithms turn a product of numbers into a sum of numbers: log(xy) = log(x) + log(y). Hyperlogarithms generalize the concept as follows: Hlog(XY) = Hlog(X) + Hlog(Y), where X and Y are any kind of objects, and the product and sum are replaced by operators in some arbitrary space. 

Source for picture:…


Added by Vincent Granville on August 16, 2017 at 12:00pm — 1 Comment

Nice Generalization of the K-NN Clustering Algorithm -- Also Useful for Data Reduction

I describe here an interesting and intuitive clustering algorithm (that can be used for data reduction as well) offering several advantages, over traditional classifiers:

  • More robust against outliers and erroneous data
  • Executing much faster
  • Generalizing well known algorithms

You don't need to know K-NN to understand this article -- but click here if you want to…


Added by Vincent Granville on August 15, 2017 at 12:00pm — No Comments

Great Saturday Reading

Here is our selection of featured articles and resources posted over the last few days:


Added by Vincent Granville on August 12, 2017 at 5:00pm — No Comments

Type I and Type II Errors in One Picture

This picture speaks more than words. It explains the concept or false positive and false negative, that is, what is referred to by statisticians as Type I and Type II errors.

Other great pictures summarizing data science and statistical concepts, can be found…


Added by Vincent Granville on August 10, 2017 at 5:17pm — No Comments

Fighting eCommerce fraud with graph technology

ECommerce fraud is growing quickly, creating new challenges in terms of prevention and detection. As merchants gather more and more information about customers and their behaviors, the key element in the fight against fraud is now to draw on the connections within the data collected to uncover fraudulent behaviors. In this post we explain why and how graph technologies are crucial in the detection of eCommerce fraud.…


Added by Elise Devaux on August 9, 2017 at 9:30am — No Comments

Great Sunday Reading

Here is our selection of new featured articles for today:


Added by Vincent Granville on August 6, 2017 at 11:33am — No Comments

Data Science Simplified: Principles and Process

In 2006, Clive Humbly, UK Mathematician, and architect of Tesco’s Clubcard coined the phrase “Data is the new oil. He said the following:

Data is the new oil. It’s valuable, but if unrefined it cannot be used. It has to be…


Added by Vincent Granville on August 3, 2017 at 4:30pm — No Comments

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