ML
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 high-performance distributed deep learning system targeting large-scale and automated distributed training.
Some Conferences' accepted paper lists (including AI, ML, Robotic)
[ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"
The goal of this library is to generate more helpful exception messages for matrix algebra expressions for numpy, pytorch, jax, tensorflow, keras, fastai.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Simple, safe way to store and distribute tensors