Tips

1. Don't try to put the cart before the horse: realize that efficient data preparation (and thus interoperable standards) and data quality, especially in the enterprise environment, are a basic requirement for…

1. Hybrid approach: Semantic AI is the combination of methods derived from symbolic AI and statistical AI. Virtuously playing the AI piano means that for a given use case various stakeholders, not only data scientists, but also process owners or subject matter experts, choose from available methods and tools, and collaboratively develop workflows that are most likely a good fit to tackle the underlying problem. For example, one can combine entity extraction based on…

DescriptiveStats.OBeu v1.2.1 release on CRAN

We are very pleased to announce DescriptiveStats.OBeu v1.2.1 on CRAN!

DescriptiveStats.OBeu is used on OpenBudgets.eu data mininig tool platform to estimate central tendency and dispersion of numeric variables along with their distributions and correlations and the…

Will Artificial Intelligence make subject matter experts obsolete?

Imagine you want to build an application that helps to identify wine and cheese pairings. Who will perform best? Applications solely based on machine learning, those ones which are based on experts' knowledge only, or a combination of both?

Most of the machine learning algorithms were…

It’s possible I haven’t shared my story of being asked whether people can leap over lampposts.  The question was posed by a university professor although I don’t recall the exact context.  In response, I asked if the people are on this planet.  He hissed at me, “Of course they are on this planet!”  Some planets have low gravitational fields that make it possible for humans to leap great heights.  At the time it didn’t seem like an oratorical question; and so I made an effort to answer it. …

Things, not Strings

Entity-centric views on enterprise information and all kinds of data sources provide means to get a more meaningful picture about all sorts of business objects. This method of information processing is as relevant to customers, citizens, or patients as it is to knowledge workers like lawyers, doctors, or researchers. People actually do not search for documents, but rather for facts and other chunks of information to bundle them up to provide answers to…

Overview

There are huge numbers of variants of deep architectures as it’s a fast developing field and so it helps to mention other leading algorithms. The list is intended to be comprehensive but not exhaustive since so many algorithms are being developed [1] [2][1],[2].

1. Deep High-order Neural Network with Structured Output (HNNSO).
2. Deep convex network.
3. Spectral networks
4. noBackTrack algorithm to solve the…

Data Science has made great strides in the last couple of decades and has promise to improve the lives of everyone. Like any technology some may view these developments to be not such a great blessing after all. I felt taking a few moments to reflect on the long-term consequences might be of some value.

I came across this post after a lapse of a season and realized…

“The Purple People” - The conundrum of finding business expertise among Data Scientists.



Over the last several months, as I looked at addressing the business needs across various industries as someone leading a team of  Data Scientists, the question of domain expertise invariably cropped up.



Attending one meeting with a Pharmaceutical company, I was posed with the question of, "Have you done work in the areas of Rare Signal detection?" In a similar vein, while…