Hands-on technical tutorials on machine learning, covering model building with Scikit-learn, Keras, TensorFlow and JAX. Each issue walks through a full project with code, datasets and Kaggle notebooks, such as LLM fine-tuning, AI text detection and CNNs.
Website: https://blog.mwiti.com/
Research posts from Redwood Research on catastrophic AI risk, focused on AI control, monitoring of agentic models, and red-teaming of safety systems. Readers get technical write-ups of papers, experiments and engagements with AI developers, including methods, results and open questions.
A personal technical newsletter from an engineer working through applied machine learning, covering model interpretability, feature engineering and cost-based decision analysis for manufacturing problems. Issues include study notes with glossaries and a worked technical memo with concrete figures and recommendations.
Weekly lessons that explain one AI engineering concept at a time, such as transformer internals, LLM inference serving and agent-based bug hunting. Each issue pairs concrete numbers and worked examples with a paid script readers can run themselves.
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.
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