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Top 23 Python ML Projects
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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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
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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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.
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deepchecks
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
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RasaGPT
💬 RasaGPT is the first headless LLM chatbot platform built on top of Rasa and Langchain. Built w/ Rasa, FastAPI, Langchain, LlamaIndex, SQLModel, pgvector, ngrok, telegram
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Photonix
A modern, web-based photo management server. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, face recognition, location awareness, color analysis and other ML algorithms.
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SaaSHub
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Ref https://www.youtube.com/watch?v=0GwnxFNfZhM https://github.com/ultralytics/yolov5 https://dev.to/gfstealer666/kaaraich-yolo-alkrithuemainkaartrwcchcchabwatthu-object-detection-3lef https://www.kaggle.com/datasets/devdgohil/the-oxfordiiit-pet-dataset/data
Project mention: What’s the Difference Between Fine-tuning, Retraining, and RAG? | dev.to | 2024-04-08Check us out on GitHub.
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It includes features for experiment tracking, model versioning, and deployment, enabling developers to track and compare experiments, package models into reproducible runs, and manage model deployment across multiple environments.
Project mention: Show HN: Toolkit for LLM Fine-Tuning, Ablating and Testing | news.ycombinator.com | 2024-04-07This is a great project, little bit similar to https://github.com/ludwig-ai/ludwig, but it includes testing capabilities and ablation.
questions regarding the LLM testing aspect: How extensive is the test coverage for LLM use cases, and what is the current state of this project area? Do you offer any guarantees, or is it considered an open-ended problem?
Would love to see more progress toward this area!
Lots of good projects on https://github.com/kelvins/awesome-mlops too
Project mention: Detect, Defend, Prevail: Payments Fraud Detection using ML & Deepchecks | dev.to | 2024-01-13Also if you have any confusion related to it. You can directly go to their discussion section in github :
Project mention: Show HN: Evaluate LLM-based RAG Applications with automated test set generation | news.ycombinator.com | 2024-04-11
Project mention: Fast Llama 2 on CPUs with Sparse Fine-Tuning and DeepSparse | news.ycombinator.com | 2023-11-23Interesting company. Yannic Kilcher interviewed Nir Shavit last year and they went into some depth: https://www.youtube.com/watch?v=0PAiQ1jTN5k DeepSparse is on GitHub: https://github.com/neuralmagic/deepsparse
RasaGPT: headless LLM chatbot platform built on top of Rasa and Langchain (https://github.com/paulpierre/RasaGPT)
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python ML related posts
- What’s the Difference Between Fine-tuning, Retraining, and RAG?
- Fine-tuning a Mistral Language Model with Anyscale
- Launch HN: Encord (YC W21) – Unit testing for computer vision models
- Show HN: Finagg – free and nearly unlimited financial data
- FLaNK 15 Jan 2024
- Detect, Defend, Prevail: Payments Fraud Detection using ML & Deepchecks
- MindsDB Docker Extension: Build ML powered apps at a much faster pace
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A note from our sponsor - InfluxDB
www.influxdata.com | 26 Apr 2024
Index
What are some of the best open-source ML projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | yolov5 | 46,921 |
| 2 | MindsDB | 21,223 |
| 3 | MLflow | 17,234 |
| 4 | best-of-ml-python | 15,302 |
| 5 | ludwig | 10,801 |
| 6 | deeplake | 7,690 |
| 7 | metaflow | 7,586 |
| 8 | CoreML-Models | 6,221 |
| 9 | feast | 5,255 |
| 10 | aim | 4,782 |
| 11 | superduperdb | 4,327 |
| 12 | zenml | 3,657 |
| 13 | awesome-mlops | 3,555 |
| 14 | polyaxon | 3,479 |
| 15 | hub | 3,436 |
| 16 | deepchecks | 3,338 |
| 17 | giskard | 3,111 |
| 18 | zvt | 2,981 |
| 19 | deepsparse | 2,873 |
| 20 | RasaGPT | 2,168 |
| 21 | ScaledYOLOv4 | 2,017 |
| 22 | GPflow | 1,794 |
| 23 | Photonix | 1,765 |
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