Naive Bias[tm] and Fairness Tooling
Just Another Dangerous Situation
A Loop to Stop Writing.
Let's make life a whole log simpler.
Maths as a Compiler
Once again, rephrasing is a friend.
Oops and Optimality
GridSearch is Not Enough: Part Five
Uncommon Contributions
Making impact without touching the core of a library.
Mean Squared Terror
GridSearch is Not Enough: Part Four
Sharing is Caring
Put Cookie-Monster on a Diet.
More Descent, Less Gradient
Your regression may only need one gradient step. Really.
Priors of Great Potential
Common Sense reduced to Priors
Introduction to Inference
Reduce Common Sense to Calculus.
Theoretical Dependence
Some assumptions are just plain weird.
The Cost of Success
VeryHighAccuracy[tm] as a Problem.
The Elephants not in the Room
The unknowns might be more interesting.
Roman Reasoning
We should evolve beyond it.
What Overfitting Looks Like
GridSearch is not enough: Part Three.
Parallel Grid
An Ode to Pipes, Seeds and Simplicity
Goodhart, Bad Metric
GridSearch is not Enough: Part Two.
Little Victories Scale
Thoughts on automating automation itself.
Outliers: Selection vs. Detection
Algorithms can detect outliers, but how do you select algorithms?
Foresight for Predictions
Predictions without Foresight can be Anticipated to become Dreadful.
Bingo Ball Pit
An Exercise in Systemic Counting
High on Probability, Low on Confidence
GridSearch is not Enough: Part One.
Some Geometric Algorithms
And Something Obvious about Albert Heijn.
The Future of Data Science is Past
And it's not just because that's whats *actually* being predicted.
Optimisation, Not Gradients
A small point to point out a difference.
Sensors are Servers
The only servers in my stack are the sensors themselves.
Wine Cellar Strategies
Pretending there's an optimal way to drink it.
VI Drives me NUTS
Feel free to be a bit weary.
Rephrasing the Billboard
A probability problem involving 40,000 sent letters.
Gaussian Auto Embeddings
Sort of came up with an alternative to VI here.
Amdahl's Law
The more CPU's you add, the worse it gets.
Feed Forward Posteriors
Combine the Neural with the Normal.
Passive Agressive Algorithms
A VeryGood[tm] name for a VeryGood[tm] Algorithm.
Vary Very Optimally
How to search in search space.
Bayesian Shaving Cream
A plausible (and general) method for model selection.
Bayesian/Streaming Algorithms
A convenient overlap.
Avoiding, and Preventing, Joins
Join me in preventing this.
Hello DeepQ
Stick a Network in the Q-learning algorithm.
Twain Learning
Never let your school get into the way of your regression.
Switching to Sampling in Order to Switch
A simple introduction to PyMC3.
Pokemon Recommendations, Part 2
Even more of a Sequel than SQL.
Lego Minifigures
An investment opportunity and sampling.
Custom Predictors in R
It's different than Python, but S3 isn't *that* bad.
Ensemble Yourself
Scribbles as an Algorithm Service.
Pokemon Recommendations, Part 1
An Attempt at an OptimalPortfolio[tm]/
Linear Models Solving Non-Linear Problems
XOR turns out to be a bad argument.
Variable Selection in Machine Learning
Merely *a* argument, but one that I like.
Digital Nomad
Some observations but also downsides.
Vanity Metrics
How I got an A+ for measuring the wrong thing.