eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Organizes 30+ categories of production ML case studies—from data quality and feature engineering to MLOps and ethical considerations—with direct links to company papers and blog posts that detail problem framing, techniques tried, scientific rationale, and measured business outcomes. The curated structure mirrors real ML project workflows, enabling practitioners to find relevant implementations across their entire pipeline rather than isolated algorithm papers. Includes supplementary Twitter summaries and cross-links to related guides on ML surveys and applied practices.
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