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Added by Andrew Marane on July 31, 2017 at 11:30am — No Comments
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…
Added by Jamilu Auwalu Adamu on July 31, 2017 at 8:30am — No Comments
Here is our list of featured articles and resources recently published on DSC:Continue
Added by Vincent Granville on July 22, 2017 at 12:41pm — No Comments
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…Continue
Added by Dan Kellett on July 21, 2017 at 1:30am — No Comments
Summary: A year ago we wrote about the emergence of fully automated predictive analytic platforms including some with true One-Click Data-In Model-Out capability. We revisited the five contenders from last year with one new addition and found the automation movement continues to move forward. We also observed some players from last year have now gone in different directions. …Continue
Added by Vincent Granville on July 18, 2017 at 11:37am — No Comments
Here is our list of featured articles and resources added today:
Added by Vincent Granville on July 15, 2017 at 1:40pm — No Comments
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…Continue
Here is our selection of articles and resources posted in the last few days.
Added by Vincent Granville on July 9, 2017 at 10:07am — No Comments
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…Continue
Added by Vivek Kalyanarangan on July 5, 2017 at 9:30pm — No Comments
Is everyone a ‘data scientist’? What about ‘data engineers’ and the junior versus senior, or skill level distinctions? We do seem to need some agreement about titling. Data Scientists is still the prestige title but there are some folks lobbying to take that title away. Click here to read more.
New blog post: 7 Great Articles About TensorFlow
Added by Vincent Granville on July 5, 2017 at 6:23pm — No Comments