Customer Lifetime Value and Its Application in Retail Analytics

Customer Lifetime Value (CLV) is a relatively new framework stemming from the idea of “treatment of customers as an asset”, in use at innovative companies like Harrah’s, IBM, and Capital One. The definition is a fairly natural one: CLV is the net present value of profit from all the future purchases a customer is going to … More Customer Lifetime Value and Its Application in Retail Analytics

Lifting the Fog on Machine Learning Maths

Confession: As a computer scientist, I have always been comfortable with discrete mathematics. However, continuous maths, especially the type commonly seen in statistical machine learning, have always been a challenge for me. In fact, I lived through the last 15 years of my professional life in a more-or-less constant fog of partial understanding when it … More Lifting the Fog on Machine Learning Maths

Privacy Preserving Outlier Detection: A Tutorial

Outlier detection is an important tool in risk modelling. In the context where data are distributed across multiple locations and data privacy is a concern, we need to start looking at privacy-preserving techniques for doing outlier detection. Linked here is a tutorial introduction to this topic I recently prepared. Privacy Preserving Outlier Detection The presentation … More Privacy Preserving Outlier Detection: A Tutorial

A Short Course on Statistical Learning

Here is a short (and somewhat unusual) course on statistical machine learning that I have delivered multiple times over the last few years. Introduction to Statistical Learning Theory Bayesian Probability Theory Sequence Prediction and Data Compression Bayesian Networks In designing this course, I have deliberately steered away from the usual practice of giving students a (long) … More A Short Course on Statistical Learning

How to Prove It

A major deficiency in many university-level computer science programs is neglect for training in fundamental mathematical skills. This deficiency usually rears its head when a CS student first move into an area like Data Science and quickly realise s/he does not even have the ability to fully understand papers and books in the field, let alone contribute … More How to Prove It