Machine learning is the branch of computer science and a subfield of Artificial Intelligence that utilizes past data to learn from and use its knowledge to make future decisions. Machine learning is at the intersection of computer science, engineering, and statistics. The goal of machine learning is to generalize a detectable pattern or to create an unknown rule from given examples.



Machine learning is broadly classified into three categories but nonetheless, based on the…

While a reliable method to accurately identify suicidal patients is missing from medical literature, researchers…

Over the past few years, an increasing protocol complexity has garnered a lot of attention among clinical trial experts. It has lead to various important studies beginning from meditating insights metrics warehouse which reveal that clinical studies have reached to a significant level of complexity in the recent times. In spite of a larger increase in metrics in the first half of the past decade and continued warnings from experts, the complexity continues to be on an upward surge through…

About a month ago in a blog, I introduced what I described as a “spectral attenuation monitor.”  At the time I only had an image from MS Works that…

Six Sigma is a quantitative approach to problem solving - to solve certain types of problems. At the root of Six Sigma is an improvement methodology that can be described by the acronym DMAIC: define, measure, analyze, improve, and control [1]. Those interested in reading up on Six Sigma might consider the book for dummies, which I found fairly succinct. Those wondering what I mean by "certain types of problems" should consider how to apply the approach to their own business circumstances. I…

I have been writing about the Crosswave Differential Algorithm for a number of years. I described in previous blogs how the algorithm emerged almost by accident while I was attempting to write an application intended to support quality control. In this blog I will be discussing the event model that powers the algorithm. Events are the details and circumstances…

A theme in my blogs is how the "structure" of data - rather than just the "content" - affects what that data can say and is capable of doing. In particular, I suggest that certain structures tend to reinforce certain contents; this means that a structural imposition can have an effect similar to a contextual imposition. Structure is an interesting conversation…

Shame on YouGov! Did their survey really miss the outcome of the Brexit consultation? Not quite. If you hit your finger while hammering a nail into the wall, do not blame the hammer.

The media circuit is responsible for having broadcasted inaccurate information. I must confirm that I am in no way linked to YouGov, the market research agency that supplied most media agencies with projections of the outcome results for the Brexit consultation in the UK, and this article…

Even today there seems to be considerable debate over the exact meaning of "stress." During my graduate studies, I pointed out that there are similar themes in the literature pertaining to stress; that perhaps researchers have been overemphasizing the differences. Among the most persistent themes is the distinction between stress and stressors. Hans Selye asserted in 1936 is that stress is an internal response against any form of noxious stimulant. He described the environmental factors…

I sometimes ask myself while musing over the need for a particular service, "I wonder if this is commercially viable?" If the service is routine and the required software is rather inexpensive, perhaps there is little need for a company to outsource. I cannot think of any company that would routinely outsource work normally performed on a spreadsheet. I suspect that decades ago some companies hired specialists to handle spreadsheets; this seems much less likely today in light of the…

Recently I spoke with a Brand Director about how to find market space he can win and defend in the long run. The discussion shifted on the meaning of information and insights and, after an interesting debate on what’s insight at all[1], we found agreement by means of an example, which I’d like to present to you too. 

From data to…

In recent blogs, I have been distinguishing between quantitative data and narrative data. I believe that I separated the two forms relatively well. Although I originally focused on the differences in data in order to give narrative "its own space," actually there can be a symbiotic relationship between the two types of data. In my last blog, I said that quantitative data can be incorporated into narrative data. In my submission today, I will be discussing how the narrative can be used to…

In this blog, I will be discussing the use of attribution models in relation to codified narrative. For this purpose, I will be referring to the plots of two films: the 1974 horror classic “The Texas Chainsaw Massacre”; and a 2014 dark comedy called “Tusk.” I have my own codification system called BERLIN: this is short for “Behavioural Event Reconstruction Linguistic Interface for Narratives.” An attribution model supports the inference of meaning from data. Imagine a student one day going…

Phenomenalism is sometimes described as a type of reductionism. Information about a complex object might be reduced to simple sensory details. For example, ignoring the many interesting features of the ice cream…

Hello and Welcome back!

This series is my attempt to start cataloging all the interesting articles, industry reports, whitepapers, and news that I read every month, related to technology and data science. We are at Month 2 and let us dig right in -

1. Network Effects, Digital Avatars and Advertising

This essay titled "…

For higher resolution, interactive Tableau charts, read original article. In this version, only static screenshots are displayed. It does not give justice to Tableau.

Coming up with a topic for today's blog post was tough. My last blog about Wine got attention from wine entrepreneurs…

This blog is about the peculiar nature in which software sometimes gets developed. I hope that many readers will recognize the relevance of data science in the examples taken from my own projects. I propose that development is the product of creativity more than accreditation. Creativity is something complicated that interacts with a person over his or her life circumstances. Many people know how to write . . . sentences and paragraphs. However, the ability to write well does not necessarily…

The role of statistics in data science is often debated. Despite rapid developments in technology giving access to algorithmically sophisticated approaches, I feel that statistics can still provide many worthwhile insights. If I have a database of sales figures spanning many years, I feel that I can become more aware of historic trends and seasonal patterns through the use of statistics. Statistics offers a sense of state, direction, pace, and progress. Statistics can also enable estimation…