Machine Learning Frontiers
Samuel FlenderReal-life lessons on ML theory, practice, and careers from a seasoned ML engineer. This is the stuff you won't learn in "standard" ML curricula.
| Platform |  | Pricing | Freemium | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 30 | Subscribers | Read | mlfrontiers.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Target Attention Is All You Need: Modeling Extremely Long User Action Sequences in Recommender Systems
Recommender systems try to predict your next action, so it may not be surprising that the most important signals going into such models are user action sequences. The best recommender systems today are consequently those that can efficientl...
Machine Learning in Fraud Detection: A Primer
Fraud detection is a cornerstone of modern e-commerce, yet it is also the perhaps least publicized domain in Machine Learning, and that’s for a good reason: it’s an adversarial domain, where fraudsters constantly invent new ways to bypass e...
Causal Modeling in Recommender Systems: A Primer
What makes us click?
The Problem With the Problem With Popularity Bias
Mitigating popularity bias has emerged as one of the major research directions in recommender systems over the recent years. At a high level, the problem this research is trying to solve is preventing ranking models from over-exploiting the...
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Authors
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Physics PhD turned ML Engineer
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