Posts
Approximate inference via variational autoencoders
A modern classic connecting probabilistic inference and deep learning.Dimensionality reduction via principal component analysis
We cover another 'classical' technique, this time for unsupervised learning.Bias-variance trade-off and the interpolating regime
Reproducing a nice result from a recent paper.Sampling b*sics
We on a roll cos ya basic.Revisiting the bias-variance decomposition
Another machine-learning classic before we move onto more advanced topics.Back to basics with Pandas
A simple end-to-end example using the scientific python stack.Mastering the basics is very underrated
Rebooting the blog with some spicy opinions.Bay Area II: CFAR Workshop
Apparently the most memorable things I learnt at CFAR were the games.Simplicity is complicated; contraints bring freedom
Ruminations on Pike, Strunk, and White.A response to 'The AI Cargo Cult'
A short rebuttal to a recent essay.AIXIjs
A web demo for general reinforcement learning.Bay Area I: San Francisco, Berkeley, & Silicon Valley
A short travel post documenting the first half of my Bay area trip.Marginalization with Einstein
In this post we explore a convenient trick for marginalizing discrete distributions in directed acyclic graphs using NumPy's Einstein summation API.Linear regression & Hello World!
A brief look at some cool results that are often overlooked in short treatments of linear regression. Also, my first blog post! Yay :)
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