A running walkthrough of An Introduction to Statistical Learning (ISLR) chapters, covering unsupervised learning, support vector machines and tree-based methods with formulas and worked examples. Readers get a study companion that restates textbook material in plain language.
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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.
Long-form essays on evaluating and specifying AI systems, drawing on hands-on projects such as a UFC judging model and an evaluation of a new model launch. Readers get practical lessons on labeling, ground truth, build-versus-buy decisions and precise AI terminology.
A weekly newsletter by a working data scientist covering the practical, often overlooked parts of data science, alongside posts on tech news and hobbies. Issues mix explanatory commentary, such as the end of leap seconds, with opinionated takes on LLMs, UX and analytics practice.
A multi-issue weekly newsletter covering machine learning and AI, including weekly industry roundups, editorials, and deep dives into research topics such as recursive self-improvement. Readers get explanations of new models, research papers, and the business dynamics of the AI industry.
One short email a week with hand-picked newsletters from the index. Free, no spam, unsubscribe anytime.
