A tutorial-style blog-newsletter explaining core machine learning concepts such as GANs, inductive logic programming, and precision versus recall. Readers get textbook-like definitions, formulas and basic examples aimed at people learning Python and ML.
Website: https://ibepyprogrammer.com/
VarOps publishes data-backed pieces on applied AI, including hands-on benchmarks of new models, critiques of how coding agents are evaluated, and tooling for agent-driven development. Each issue includes disclosures, concrete numbers, and tests readers can run on their own data or history.
This newsletter publishes in-depth technical explainers on machine learning systems, covering LLM architecture, inference costs, and agent infrastructure. Readers get conceptual breakdowns with concrete examples drawn from recent model releases and platform APIs.
Ivan Zdravkov publishes pre-registered AI experiments with transparent gates and reported numbers, covering LLM-as-a-judge reliability, API versus local model economics, and continual learning with EWC. The newsletter explains what each experiment tested and what its results do and do not show.
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