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Featured Blog Posts (1,462)

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 — 1 Comment

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 — 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…

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

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 — No Comments

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 — No Comments

How to Detect if Numbers are Random or Not

In this article, you will learn some modern techniques to detect whether a sequence appears as random or not, whether it satisfies the central limit theorem (CLT) or not -- and what the limiting distribution is if CLT does not apply -- as well as some tricks to detect abnormalities. Detecting lack of randomness is also referred to as signal versus noise detection, or pattern recognition.

It leads to the exploration of time series with massive, large-scale (long term) auto-correlation…

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Added by Vincent Granville on July 10, 2017 at 12:00am — 4 Comments

Open sourcing 'spot the difference'

Capital One UK’s Data Science team has been focused on move from proprietary (paid-for) software to open source for some time now.

There are several key benefits to making this change. Open source software is prevalent in academia which makes it much easier for our new starters to hit the ground running, building models and analysing data on day one with the company (the switch has also been a terrific development opportunity for my team to learn new skills). Our team now has greater…

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Added by Dan Kellett on July 21, 2017 at 1:30am — No Comments

Text Clustering : Get quick insights from Unstructured Data

In this two-part series, we will explore text clustering and how to get insights from unstructured data. It will be quite powerful and industrial strength. The first part will focus on the motivation. The second part will be about implementation.

This post is the first part of the two-part series on how to get insights from unstructured data using text clustering. We will build this in a very modular way so that it can be applied to any dataset. Moreover, we will also focus…

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Added by Vivek Kalyanarangan on July 5, 2017 at 9:30pm — No Comments

For Companies, Data Analytics is a Pain; But Why?

Businesses across the globe are facing the brunt, one of huge data influx and second of increasing data complexity and of course the market volatility. To address these challenges, companies and all their verticals are turning to data-driven analytics and insights as a means to better understand their organization’s customer bases and to grow their businesses; and manage the increasing uncertainty up to a certain extent. 

The shift from conventional…

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Added by Chirag Shivalker on June 22, 2017 at 1:30pm — No Comments

Descriptive, Predictive & Prescriptive Analytics will fail to Help You Understand Your Business

It has been a practice followed religiously by companies and organizations to analyze how they have performed over a…

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Added by Chirag Shivalker on May 12, 2017 at 7:30am — No Comments

Business Analytics and Intelligence Compared

Business analytics and business intelligence are two different notions, but only few people understand the difference. Interestingly, even people who have worked in the business industry struggle with this particular topic or have various different answers when someone asks the question 'What is the difference between business analytics and business intelligence?'

Some people define business analytics as an umbrella term and place intelligence as one of its parts, together with data…

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Added by Laura Buckler on April 25, 2017 at 8:00am — 1 Comment

12 Interesting Reads for Math Geeks

Many data scientists have a passion for mathematics, and many modern math problems can be explored using data science. Below is a selection of interesting articles, many about challenging, deep mathematical problems, by a data scientist who developed math-free algorithms. Some of these articles cover statistical theory and thus belong to data science,…

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Added by Vincent Granville on May 3, 2017 at 11:30am — No Comments

16 Data Science Repositories

Each one is a repository in its own, and they cover topics such as time series, regression, outliers, clustering, correlation, Hadoop, deep learning, Python, IoT, data sets, cheat sheets, infographics, and more (AI coming soon.) 

Each one features a number of popular articles and resources.

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Added by Vincent Granville on May 3, 2017 at 10:00am — No Comments

The Ultimate Guide for Choosing Algorithms for Predictive Modeling

There are three ways to look at data. The first is analytics. This is when you look at data from the (potentially very recent) past. Think analytics. It allows you to explore the questions what happened and why did it happen? The second is monitoring. This is looking at things as they happen. In many…

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Added by Steven M. Mehler on April 3, 2017 at 12:00am — 1 Comment

Monte Carlo Analysis and Simulation

The Monte Carlo method is an simple way to solve very difficult probabilistic problems. This text is a very simple, didactic introduction to this subject, a mixture of history, mathematics and mythology.

 

The method has origins in the World War II, proposed by the Polish American mathematician Stanislaw Ulam and Hungary American mathematician John Von Neumann.…

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Added by Arnaldo Gunzi on April 11, 2017 at 4:00pm — No Comments

4 types of social media analytics explained

Depending on the business objectives, social media analytics can take four different forms, namely, descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Social media data is the new gold and analytics is its digging tool. Social Media Analytics (SMA) is the art and science of extracting valuable hidden business insights from social media media data (Khan, 2015) . SMA turns the…

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Added by Gohar Feroz Khan on April 10, 2017 at 1:30pm — No Comments

Tips for Reducing Fraud and Bolstering Customer Data Security

Many businesses, especially small businesses, underestimate the danger their company’s data is in. They have the idea that because they’re fairly small, no one would want to try to steal the customer information they collect. After all, why go after a few thousand customer records when you could attack a large corporation and potentially walk away with tens of…

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Added by Peter Davidson on April 17, 2017 at 6:00am — No Comments

Factoring Massive Numbers: Machine Learning Approach - Why and How

We are interested here in factoring numbers that are a product of two very large primes. Such numbers are used by encryption algorithms such as RSA, and the prime factors represent the keys (public and private) of the encryption code. Here you will also learn how data science techniques are applied to big data, including visualization, to derive insights. This article is good reading for the data scientist in training, who might not necessarily have easy access to interesting data: here the…

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Added by Vincent Granville on April 6, 2017 at 7:30pm — No Comments

Math Challenge: Computing the Average Rotational Speed of Earth

Or of any celestial body. Here I discuss a solution that can be explained to high school students, to get them interested in mathematics, statistics and probabilities. A few interesting related problems further enhance the pedagogical value of this discussion.  

I stumbled upon this kind of problems when learning advanced mathematics in my postgraduate studies, in a course entitled stochastic geometry. Just formulating the problem required advanced knowledge of sophisticated…

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Added by Vincent Granville on March 3, 2017 at 1:00am — No Comments

In Japan, "Artificial Intelligence" comes to be a super star while "Data Scientist" is fading away

I published a post about the current status of "Data Scientist" in Japan, as a periodic follow-up analysis since two years ago. Its trend still remains, but it's beyond my anticipation at that time.

Indeed growing trend of "Artificial Intelligence" in Japan is steeper than…

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Added by Takashi J. OZAKI on January 13, 2017 at 6:30am — 1 Comment

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