rapids
There are 4 repositories under rapids topic.
- Language:C++ 7416
graphistry / pygraphistry
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
Language:Python 2066- blazingsql
BlazingDB / blazingsql
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
Language:C++ 1906 - Language:Cuda 1585
- Language:Scala 728
- kglab
DerwenAI / kglab
Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, NetworkX, RAPIDS, RDFlib, pySHACL, PyVis, morph-kgc, pslpython, pyarrow, etc.
Language:Jupyter Notebook 561 - Language:C++ 432
- cuxfilterLanguage:Python 265
- Language:Python 111
- fractional_differencing_gpu
ritchieng / fractional_differencing_gpu
Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.
Language:Jupyter Notebook 55 HROlive / Applications-of-AI-for-Predictive-Maintenance
Nvidia DLI workshop on AI-based predictive maintenance techniques to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding parts, and map anomalies to failure conditions.
Language:Jupyter Notebook 21- Welcome_to_BlazingSQL_Notebooks
RAPIDS data science. No setup required.
Language:Jupyter Notebook 19 Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.
Language:Jupyter Notebook 16KAUST-Academy / nvidia-rapids-data-science-project
Template repository for a Python 3-based (data) science project with GPU acceleration using NVIDIA RAPIDS libraries.
Language:Shell 8gdaisukesuzuki / PKGBUILD_Rapids
Building NVIDIA's RAPIDS (cuDF, cuML...) in Arch Linux
Language:Jupyter Notebook 7- Language:Jupyter Notebook 7
The Incredible RAPIDS: a curated list of tutorials, papers, projects, communities and more relating to RAPIDS.
bhattbhavesh91 / cuDF-RAPIDS-demo
A simple demo of cuDF which is a RAPIDS GPU-Accelerated Dataframe Library!
Language:Jupyter Notebook 6- Language:Jupyter Notebook 6
gumdropsteve / turbo-telegram
GPU accelerated Jupyter dashboard.
Language:Jupyter Notebook 5fdasilva59 / Docker-AI
Easily build a customizable, ready to use Docker Image for some AI/Data Science/Deep Learning experiments.
Language:Shell 3- Language:Jupyter Notebook 3
jantra-io / jantra-rapids-and-rivers
Rapids and rivers pattern interpretation and implementation
Language:Kotlin 1mariamkhmahran / higgs-boson-discrimination
GPU-based ML to classify Higgs boson signal from background in particle physics using RAPIDS framework
Language:Jupyter Notebook 1RazHoshia / Wids2021EvalMLRapids
combination of EvalML with Rapids for the WiDS 2021 competition
Language:Python 1ghadikq / Mortgage_Prediction
Predict loan amount using RAPIDS libraries.
Language:Jupyter Notebook 0mhmatsumura / Ciencia_De_Dados
Códigos PYTHON. Pandas, Scikit-Learning, Rapids, Cuml, Cudf.
Language:Jupyter Notebook 0Running KNN algorithm much faster on GPU for free using RAPIDS packages like cuML and cuDF
Language:Jupyter NotebookExample notebooks using BlazingSQL with the RAPIDS AI ecoystem.
Language:Jupyter Notebooktaher-software / Shopee---Price-Match-Guarantee
Shopee is the leading e-commerce platform in Southeast Asia and Taiwan. Customers appreciate its easy, secure, and fast online shopping experience tailored to their region. The company also provides strong payment and logistical support along with a 'Lowest Price Guaranteed' feature on thousands of Shopee's listed products. In this competition, we had been requested to build a model that predicts which items are the same products for Shopee company.
Language:Jupyter Notebook
