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

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain

Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://amzn.to/3JUgR2L

Attempting to replicate "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem" https://arxiv.org/abs/1706.10059 (and an openai gym environment)

Here you can find all the Tutorials for Haystack 📓

A repository for my PyCon talk: "Building a personal assistant with Haystack and GPT: How to feed facts to large language models and reduce hallucinations"