True Theta Substack
DJ, Howe WangWe bridge the gap between data and effective decision-making with time-tested, custom-built algorithms.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 13 | Founded | 2 years ago | Last Issue | 3 months ago |
| Active | |||||
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truetheta.substack.comLatest Issues
How to Understand Recommender Systems
This was originally posted June 2024
In this post, I’ll present a perspective for understanding recommender systems. At their core is a model that infers users’ preferences for items, which are then used to recommend those that are...
Contextual Bandits as Supervised Learning
Originally published on truetheta.io June 2024
Contextual bandit algorithms are arguably[1] some of the most profitable form of reinforcement learning deployed in the real world. Concretely, in Agarwal et al (2017), the Microsoft t...
Model Collapse
Today, we consider the reality: synthetic content is flooding the internet, and that makes it harder for models to learn from the real world.
Studies show that models trained too heavily on their own outputs begin to lose rare informa...
Should You Retrain That Model? (Part 3)
In Part 1, we explored the challenges of model degradation, including how it often goes unnoticed and why teams hesitate to retrain due to factors like shifting priorities. In Part 2, we discussed reframing the retraining decision as a prac...
Should You Retrain That Model? (Part 2)
In Part 1, we laid out the problem: models degrade silently, teams delay retraining, and the standard "monitor for drift" approach falls short as a decision policy. Here in Part 2, we'll reframe that question as a counterfactual comparison...
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Authors
The writers behind this newsletter.
I help companies build machine learning models.
I write about public technology spending, machine learning infrastructure, and enterprise AI adoption
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