What you need to know about data augmentation for machine learning
Plentiful high-quality data is the key to great machine learning models. But good data doesn’t grow on trees, and that …
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A simple workflow for deep learning
As a follow-up to my Primer On Universal Function Approximation with Deep Learning, I’ve created a project on Github that …
A primer on universal function approximation with deep learning (in Torch and R)
Arthur C. Clarke famously stated that “any sufficiently advanced technology is indistinguishable from magic.” No current technology embodies this statement …
Lead your own data science projects with the 3 Ps
There’s a lot of literature on learning the technical aspect of data science: statistics, machine learning, data munging, big data. …
Best practices for logging computational systems in R and Python
As is the case with most quant software, it’s a bit different from run-of-the-mill software. The somewhat prosaic world of …
How to write good tests in R
Testing is an often overlooked yet critical component of any software system. In some ways this is more true of …
Modeling data with functional programming – State based systems
UPDATE: This draft is obsolete. Please see latest draft at I’m pleased to announce the availability of my latest chapter …
Rosie the Robot vs Roomba: Two Views on AI
This site generously supported by Datacamp. Datacamp offers a free interactive introduction to R coding tutorial as an additional resource. …
Using Occam’s Razor to solve genius math puzzles
Math puzzles always tickle the brain, and this one has tickled quite a few on LinkedIn. Why are these puzzles …
Is deep learning a Markov chain in disguise?
Andrej Karpathy’s post “The Unreasonable Effectiveness of Recurrent Neural Networks” made splashes last year. The basic premise is that you …
Cartesian Faith 