datascience.fm publishes practical data science and AI write-ups, including hands-on notes on running LLM sentiment analysis in PySpark and blueprints for recommendation feeds on AI platforms. Readers get concrete ideas and workflow reflections, though the issues vary between personal experiments and more generic product proposals.
Website: https://datascience.fm/
TheSequence is a publication covering machine learning, AI, and data science, with weekly-style editorial pieces, research deep dives such as recursive self-improvement and learned update rules, and AI industry analysis. Readers get concise explanations of AI research developments, business news, and robotics coverage.
Counting Stuff is a weekly newsletter by a data scientist that blends practical explanations of everyday data science work with personal essays on hobbies and technology. Recent issues cover why LLMs struggle with usable interface design, how data scientists find predictive signal, and how autumn foliage is measured through observation, remote sensing and models.
A practical data-science newsletter from Rad Sports Analytics covering college football rating methods, opponent adjustment, and Python tutorials with reusable resources. Issues walk through building ratings step by step and compare how different team-strength measures disagree.
DataChef is an Amsterdam big-data consultancy whose blog covers AI adoption in organizations, engineering write-ups of its own product features, and methodology for ranking AI models in Dutch. The excerpts combine opinion pieces on operating models with detailed technical walkthroughs of ranking algorithms and recommender design.
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