Data notes

Forwarded from Artem Ryblov’s Data Science Weekly

ML and LLM system design: 500 case studies to learn from

How do companies like Netflix, Airbnb, and Doordash apply AI to improve their products and processes? We put together a database of 500 case studies from 100+ companies that share practical ML use cases, including applications built with LLMs and Generative AI, and learnings from designing ML and LLM systems.

Navigation tips. You can play around with the database by filtering case studies by industry or ML use case. We added tags based on recurring themes. This is not a perfect or mutually exclusive division, but you can use the tags to quickly find:
- Generative AI use cases. Look for tags “generative AI” and “LLM” to find examples of real-world LLM applications.
- ML systems with different data types: computer vision (CV) or natural language processing (NLP).
- ML systems for specific use cases. The most popular are recommender systems, search and ranking, and fraud detection.
- We also labeled use cases where ML powers a specific user-facing "product feature": from grammatical error correction to generating outfit combinations.

Link: Site

Navigational hashtags: #armknowledgesharing #armsites
General hashtags: #mlsystemdesign #ml #systemdesign #llm

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93 viewsDec 5, 2024 at 02:44

ML and LLM system design: 500 case studies to learn from

How do companies like Netflix, Airbnb, and Doordash apply AI to improve their products and processes? We put together a database of 500 case studies from 100+ companies that share practical ML use cases, including applications built with LLMs and Generative AI, and learnings from designing ML and LLM systems.

Navigation tips. You can play around with the database by filtering case studies by industry or ML use case. We added tags based on recurring themes. This is not a perfect or mutually exclusive division, but you can use the tags to quickly find:
- Generative AI use cases. Look for tags “generative AI” and “LLM” to find examples of real-world LLM applications.
- ML systems with different data types: computer vision (CV) or natural language processing (NLP).
- ML systems for specific use cases. The most popular are recommender systems, search and ranking, and fraud detection.
- We also labeled use cases where ML powers a specific user-facing "product feature": from grammatical error correction to generating outfit combinations.

Link: Site

Navigational hashtags: #armknowledgesharing #armsites
General hashtags: #mlsystemdesign #ml #systemdesign #llm

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