Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Open source platform for the machine learning lifecycle
Open standard for machine learning interoperability
Low-code framework for building custom LLMs, neural networks, and other AI models
Build, Manage and Deploy AI/ML Systems
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
Largest list of models for Core ML (for iOS 11+)
The Open Source Feature Store for AI/ML
Open-source observability for your LLM application, based on OpenTelemetry
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
Superduper: End-to-end framework for building custom AI applications and agents.
ZenML 🙏: The bridge between ML and Ops. https://zenml.io.
😎 A curated list of awesome MLOps tools
Snips Python library to extract meaning from text
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.
modular quant framework.
A library for transfer learning by reusing parts of TensorFlow models.
The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.
💬 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
nannyml: post-deployment data science in python