recs-at-resonable-scale
mlops-python-package
| recs-at-resonable-scale | mlops-python-package | |
|---|---|---|
| 2 | 1 | |
| 218 | 353 | |
| - | - | |
| 2.3 | 7.4 | |
| about 1 year ago | about 2 months ago | |
| Python | Jupyter Notebook | |
| MIT License | Creative Commons Attribution 4.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
recs-at-resonable-scale
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When writing ML software - how do you use TDD?
Good paper, and in response to that one a team from Coveo, wrote this paper on behavioral tests for recommender systems... and also this repo.
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Creating Personalize Recommendation System Design
Check out RecSys (and while you're at it, if experiment tracking is your thing, try integrating with Comet)
mlops-python-package
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When writing ML software - how do you use TDD?
I always use TDD when I work on serious AI/ML projects. Even if this practice is time-consuming in the short term, it's time efficient in the long run. I prefer to catch bugs as early as possible in my workflow. I recently worked on a MLOps Python package that provides examples to implement best practices like TDD, code coverage and more: https://github.com/fmind/mlops-python-package
What are some alternatives?
Transformers4Rec - Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
superduperdb - 🔮 SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai