Streamlit — A faster way to build and share data apps.
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Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
- machine-learning
- models
- ui
- ui-components
:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.
Visualizer for neural network, deep learning and machine learning models
🕸️ Web apps in pure Python 🐍
- python
- framework
- open-source
- gui
1,324-exercise fitness dataset — animation GIFs, 180×180 thumbnails, muscle-group & equipment data, and step-by-step instructions in 6 languages. The exercise data layer behind the LogPress app.
- fitness
- fitness-app
- dataset
- exercise-database
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
- notebooks
- python
- data-science
- machine-learning
Turns Data and AI algorithms into production-ready web applications in no time.
:satellite: Simple and ready-to-use tutorials for TensorFlow
- tensorflow
- python
- deep-learning
- deep-learning-tutorial
🦉 Data Versioning and ML Experiments
- data-science
- machine-learning
- reproducibility
- data-version-control
StableLM: Stability AI Language Models
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
- agent
- ai
- automation
- data-mining
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- computer-vision
- deep-learning
- drug-discovery
- forecasting
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
High-Resolution Image Synthesis with Latent Diffusion Models
Relocate resource intensive third-party scripts off of the main thread and into a web worker. 🎉
- webworker
- 3rd-party
- 3rdparty
- web-worker
PyTorch code and models for the DINOv2 self-supervised learning method.
Practice your pandas skills!
- pandas
- jupyter-notebooks
- pandas-tutorial
- python-pandas
机器学习相关教程
Session replay, cobrowsing and product analytics you can self-host. Best for reproducing issues and iterating on your product.
A Library for Advanced Deep Time Series Models for General Time Series Analysis.
PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)
- pytorch
- pytorch-tutorials
- pytorch-tutorials-cn
- deep-learning
AI Observability & Evaluation
- llmops
- ai-monitoring
- ai-observability
- llm-eval
Foundational Models for State-of-the-Art Speech and Text Translation