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
Colleagues and friends often ask me for book recommendations on data science. Here are seven books that teach some of the most important mental models on the limits of predictability and model building, as well as prediction techniques that actually work in practice. An Introduction to Probability and Inductive Logic by Ian Hacking Against the Gods: … More A Reading List for Data Scientists
I have been studying and experimenting with online learning algorithms for support vector machines (SVMs) for a while now, primarily with the intention of understanding how they can be used to learn SVM models on large multi-terabyte datasets. The following technical report describes the NORMA and PEGASOS family of algorithms and give some observations and relevant … More Online Support Vector Machines
A colleague recently came back from his MBA class with a useful insight: Agile practices work like a (financial) leverage in project management, magnifying good things on the way up and bad things on the way down. There are already many good books and articles on the benefits of agile software engineering and agile data science so … More Agile Data Science – A Prerequisite
In this set of notes, I derive the common Bayesian estimators for Bernoulli distributions like the Laplace estimator and the Krichevsky-Trofimov estimator. Notes on Bayesian Estimators for Bernoulli Distributions
I spent a year working in Mumbai, India (May 2012 to May 2013). Here are some photos from that year. Housing We lived in an apartment at Powai. It’s a nice-enough place, as long as you don’t mind termites in the house, crocodiles in the lake, and leopards in the surrounding hills. (Leasing a place in … More India – A Photo Diary
Partial Least Squares (PLS) is a widely used technique in chemometrics, especially in the case where there is multi-collinearity in the set of variables; the number of variables is larger than the number of data points; and there are multiple response variables. There are many articles on PLS but the mathematical details of PLS do … More Partial Least Squares Explained
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
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
The Macau gaming stocks have been smashed in the last 18 months, down 70% in certain cases. The following chart, which shows the Macau Gross Gaming Revenue (in units of MOP million) as published by Macau’s Gaming Inspection and Coordination Bureau, shows the underlying problem: since early 2014, the total Macau gaming revenue has dropped … More SJM Holdings — A Value Play
Mental Models 4 Life 