Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
-
Updated
May 18, 2024 - Python
Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
Merlin Models is a collection of deep learning recommender system model reference implementations
Accelerated vector search using RAPIDS cuVS.
A full pipeline AutoML tool for tabular data
This repository consists for gpu bootcamp material for HPC and AI
Comparison of Dataframe libraries for parallel processing of large tabular files on CPU and GPU.
Multi-Objective Recommender System
Awesome list of alternative dataframe libraries in Python.
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
Running KNN algorithm much faster on GPU for free using RAPIDS packages like cuML and cuDF
Colab notebooks exploring different Machine Learning topics.
This container is no longer supported, and has been deprecated in favor of: https://github.com/joehoeller/NVIDIA-GPU-Tensor-Core-Accelerator-PyTorch-OpenCV
Objective of the repository to play around with different tools (keepsake, MLflow etc) with basic projects.
This repositorty will contain the code and slides for PyBay2020 talk: Scalable Hyper-parameter Optimization using RAPIDS and AWS
Add a description, image, and links to the rapidsai topic page so that developers can more easily learn about it.
To associate your repository with the rapidsai topic, visit your repo's landing page and select "manage topics."