Learn how to design, develop, deploy and iterate on production-grade ML applications.

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

A Toolbox for Adversarial Robustness Research

A newer more updated version of the prometheus anomaly detector (https://github.com/AICoE/prometheus-anomaly-detector-legacy)

End to end MLRun demos

MLRun template functions and examples

Build Train and Deploy your own custom container using AWS StepFunctions Data Science SDK