BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.

This repository consists for gpu bootcamp material for HPC and AI

A full pipeline AutoML tool for tabular data

Merlin Models is a collection of deep learning recommender system model reference implementations

This container is no longer supported, and has been deprecated in favor of: https://github.com/joehoeller/NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV

Awesome list of alternative dataframe libraries in Python.

Colab notebooks exploring different Machine Learning topics.

A Kedro plugin that provides pandas dropin replacements for the pandas datasets (e.g modin and cuDF)

Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.

This repositorty will contain the code and slides for PyBay2020 talk: Scalable Hyper-parameter Optimization using RAPIDS and AWS

Comparison of Dataframe libraries for parallel processing of large tabular files on CPU and GPU.

Objective of the repository to play around with different tools (keepsake, MLflow etc) with basic projects.

Multi-Objective Recommender System

Accelerated vector search using RAPIDS cuVS.

combination of EvalML with Rapids for the WiDS 2021 competition

Kaggle Tabular Feb 2022

Running KNN algorithm much faster on GPU for free using RAPIDS packages like cuML and cuDF