vorobeevich/ml-snippets-classification
The source code of "Machine learning code snippets semantic classification" (Valeriy Berezovskiy, Anastasia Gorodilova, Ekaterina Trofimova, Andrey Ustyuzhanin) paper.
This project helps machine learning researchers and data scientists categorize code snippets by their semantic meaning. By inputting raw machine learning code, you get classifications that indicate what task the code performs. This is ideal for those who study or work with large datasets of ML code and need to understand its function at a high level.
No commits in the last 6 months.
Use this if you are analyzing a large collection of machine learning code and need to automatically identify the purpose or task of individual code snippets.
Not ideal if you need to understand the detailed logic within a single code snippet or if your code is not related to machine learning tasks.
Stars
12
Forks
4
Language
Python
License
MIT
Category
Last pushed
Oct 27, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/vorobeevich/ml-snippets-classification"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
SwanHubX/SwanLab
⚡️SwanLab - an open-source, modern-design AI training tracking and visualization tool. Supports...
mdsrqbl/omnihuman
AI model that understands text & humanoids.
stas00/ml-engineering
Machine Learning Engineering Open Book
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including...
analyticalrohit/AI-ML-Cheatsheets
All Stanford Cheatsheets: Artificial Intelligence, Transformers, LLMs, Deep Learning, Machine...