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Great Sunday Reading

Here is our list of featured articles and resources posted in the last few days:

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Added by Vincent Granville on September 9, 2017 at 4:22pm —
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Building Convolutional Neural Networks with Tensorflow

In the past year I have also worked with Deep Learning techniques, and I would like to share with you how to make and train a Convolutional Neural Network from scratch, using tensorflow. Later on we can use this knowledge as a building block to make interesting Deep Learning applications.

The pictures here are from the full article. Source code is also provided.…

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Added by ahmet taspinar on September 7, 2017 at 7:30am —
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A Day in the life of an Analyst

A typical day in the life of an Analyst

An Analyst works on varied projects with multiple deliverables and varied duties depending on the business objectives.

However there are some tasks that can be easily classified as “common everyday duties” in a “typical work day of a business analyst”

Clarification and…

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Added by Ivy Pro School on September 3, 2017 at 2:00pm —
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Great Sunday Reading

Here is our list of recently featured articles and resources. The most recent are at the top.

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Added by Vincent Granville on September 3, 2017 at 11:46am —
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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…

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

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Added by Vincent Granville on August 30, 2017 at 7:30pm —
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Great Sunday Reading

The following articles and resources were featured today:

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Added by Vincent Granville on August 27, 2017 at 12:10pm —
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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.…

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Added by Vincent Granville on August 24, 2017 at 5:30pm —
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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…

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Added by Vincent Granville on August 23, 2017 at 2:30pm —
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8 Great Articles, Tutorials, and Infographics

Posted on DSC today and yesterday

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Added by Vincent Granville on August 22, 2017 at 12:39pm —
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Great Friday Reading

Here is our list of newly featured articles and resources:

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Added by Vincent Granville on August 18, 2017 at 8:50pm —
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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. …

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

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Added by Vincent Granville on August 15, 2017 at 12:00pm —
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Great Saturday Reading

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

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Added by Vincent Granville on August 12, 2017 at 5:00pm —
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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…

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Added by Vincent Granville on August 10, 2017 at 5:17pm —
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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.…

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Added by Elise Devaux on August 9, 2017 at 9:30am —
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Great Sunday Reading

Here is our selection of new featured articles for today:

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Added by Vincent Granville on August 6, 2017 at 11:33am —
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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…

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Added by Vincent Granville on August 3, 2017 at 4:30pm —
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Introducing User Behavioral Analysis in the Risk Process

Many years ago when I was entering the intelligence community, I attended a class in Virginia where the instructor opened the session with a test that I will never forget and that I have applied to almost every analytic task in my career. At the beginning of the class we were shown a ten-minute video of grand central station at rush hour with tens of thousands of people and were asked if we could find a single pickpocket in the crowd by the end of the video.  At the end of ten minutes no…

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Added by Andrew Marane on July 31, 2017 at 11:30am —
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Capturing Low-Probability, High-Impact Events ‘Black Swans’ in Economic and Financial Models

Capturing Low-Probability, High-Impact Events ‘Black Swans’ in Economic and Financial Models
Jamilu Auwalu Adamu , Lecturer, Nigeria

Incorporation of Fat – Tailed Effects of the Underlying Assets Probability Distribution using Advanced Stressed Methods.

Capturing the effects of Low-Probability, High-Impact “Black Swans” in the existing stochastic and deterministic models is tremendously…

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Added by Jamilu Auwalu Adamu on July 31, 2017 at 8:30am —
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