Quantifying the Accuracy of Business Rules

Telcos everywhere are working on initiatives to better monetise their data. For many of them, a key challenge in addressing customer requirements is lack of labelled data. For example, a customer may come along and make a request: “Tell me something about the shopping behaviour of housewives in the country”. This seemingly simple question is actually … More Quantifying the Accuracy of Business Rules

A Note on Lazy Evaluation in R

R is commonly thought of as a functional programming language. If you associate functional programming (FP) with lambda calculus and pure FP languages like Haskell, then you may get surprised by aspects of R’s computational model. One of these has to do with R’s lazy evaluation mechanism, in particular the concept of “promise objects” (as pointed out by some, … More A Note on Lazy Evaluation in R

On Data Science Training — Core Technical Skills

I have given quite a few data science training courses over the years and those conducted for industry participants are, without a doubt, the most challenging ones. There are a few reasons: The training course tends to be quite short — between 3-5 days typically — so the trade-offs between depth and breadth, between theory and … More On Data Science Training — Core Technical Skills