Python Gpu-dataframe Resources

(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify

jax-multi-gpu-resnet50-example This repo shows how to use jax for multi-node multi-GPU training. The example is adapted from the resnet50 example in d

NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

napari-cupy-image-processing GPU-accelerated image processing using cupy and CUDA This napari plugin was generated with Cookiecutter using with @napar

General purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabled, asynchronous and optimized for advanced GPU data processing usecases. Backed by the Linux Foundation.

TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c

NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs. It enables data scientists, machine

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

impy is All You Need in Image Analysis impy is an all-in-one image analysis library, equipped with parallel processing, GPU support, GUI based tools a

TorchArrow (Warning: Unstable Prototype) This is a prototype library currently under heavy development. It does not currently have stable releases, an

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

Tablexplore is an application for data analysis and plotting built in Python using the PySide2/Qt toolkit.

This repository contains code to containerize and deploy a GPU docker on AWS for summarization task. Find a detailed blogpost here Youtube Video Versi

Blue noise image stippling in Processing (requires GPU)

Face Recognition GUI This repository is a GUI version of Face Recognition by Adam Geitgey, where e.g. Docker and Tkinter are utilized. All the materia

Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.

BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

Transformer in Triton (wip) Implementation of a Transformer, but completely in Triton. I'm completely new to lower-level neural net code, so this repo

streamdf Streamdf is a lightweight data frame library built on top of the dictionary of numpy array, developed for Kaggle's time-series code competiti

Pretty GeoDataFrame A minimum python function (~60 lines) to draw pretty geodataframe. Based on matplotlib, shapely, descartes. Installation just use

WarpDrive is a flexible, lightweight, and easy-to-use open-source reinforcement learning (RL) framework that implements end-to-end multi-agent RL on a single GPU (Graphics Processing Unit).

NEWLY ADDED A3G A NEW GPU/CPU ARCHITECTURE OF A3C FOR SUBSTANTIALLY ACCELERATED TRAINING!! RL A3C Pytorch NEWLY ADDED A3G!! New implementation of A3C

Web Scrapper Projeto desenvolvido em python, sobre tudo com Selenium, BeautifulSoup e Pandas é um web scrapper que puxa uma tabela com as principais e

Binance history data downloader Download history data from binance and save to dataframe or csv file

Gradient Cache Gradient Cache is a simple technique for unlimitedly scaling contrastive learning batch far beyond GPU memory constraint. This means tr

ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p

Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R

Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.

A curated list of amazingly awesome Cybersecurity datasets

PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp

GPU-accelerated PyTorch implementation of Zero-shot User Intent Detection via Capsule Neural Networks This repository implements a capsule model Inten

​ DS2.ai is an integrated AI operation solution that supports all stages from custom AI development to deployment. It is an AI-specialized platform service that collects data, builds a training dataset through data labeling, and enables automatic development of artificial intelligence and easy deployment and operation.

Py2CUDA Convert python code to CUDA. Usage To convert a python file say named py_file.py to CUDA, run python generate_cuda.py --file py_file.py --arch

Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv

MentisOculi Pytorch Path Tracer A very simple and small path tracer written in pytorch meant to be run on the GPU Why use pytorch and not some other c

ocaml-torch provides some ocaml bindings for the PyTorch tensor library. This brings to OCaml NumPy-like tensor computations with GPU acceleration and tape-based automatic differentiation.

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

Bearsql adds sql syntax on pandas dataframe. It uses duckdb to speedup the pandas processing and as the sql engine

QPT - Quick packaging tool 快捷封装工具 GitHub主页 | Gitee主页 QPT是一款可以“模拟”开发环境的多功能封装工具，一行命令即可将普通的Python脚本打包成EXE可执行程序，与此同时还可轻松引入CUDA等深度学习加速库， 尽可能在用户使用时复现您的开发环境。

U Net Lowered with Keras Complete U-net Implementation with keras Original Paper Link : https://arxiv.org/abs/1505.04597 Special Implementations : The

DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters

Newegg Shuffle Python module(s) to help you with the Newegg raffle How to use $ git clone https://github.com/Matthew17-21/Newegg-Shuffle $ cd Newegg-S

PyToQlik is a library that allows you to integrate Qlik Desktop with Jupyter notebooks. With it you can: Open and edit a Qlik app inside a Ju

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

An interactive NVIDIA-GPU process viewer, the one-stop solution for GPU process management.

A lightweight (serverless) native python parallel processing framework based on simple decorators and call graphs, supporting both control flow and dataflow execution paradigms as well as de-centralized CPU & GPU scheduling.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Efficient implementations of Product Quantization and its variants using Pytorch and CUDA

🤗 Accelerate was created for PyTorch users who like to write the training loop of PyTorch models but are reluctant to write and maintain the boilerplate code needed to use multi-GPUs/TPU/fp16.

This repo contains a selection of projects designed to help you learn the basics of computer graphics. We'll be writing shaders to render interactive two-dimensional and three-dimensional scenes.

[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

monolish is a linear equation solver library that monolithically fuses variable data type, matrix structures, matrix data format, vendor specific data transfer APIs, and vendor specific numerical algebra libraries.

An open-source library of algorithms to analyse time series in GPU and CPU.

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr

ipyexperiments jupyter/ipython experiment containers and utils for profiling and reclaiming GPU and general RAM, and detecting memory leaks. About Thi

SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1

GPUtil GPUtil is a Python module for getting the GPU status from NVIDA GPUs using nvidia-smi. GPUtil locates all GPUs on the computer, determines thei

Vulkan Kompute The general purpose GPU compute framework for cross vendor graphics cards (AMD, Qualcomm, NVIDIA & friends). Blazing fast, mobile-enabl

A lightweight, GPU accelerated, SQL engine built on the RAPIDS.ai ecosystem. Get Started on app.blazingsql.com Getting Started | Documentation | Examp

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

NVIDIA DALI The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provi

py3nvml Documentation also available at readthedocs. Python 3 compatible bindings to the NVIDIA Management Library. Can be used to query the state of

cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Resources cuDF Reference Documentation: Python API refe

Package Description scikit-cuda provides Python interfaces to many of the functions in the CUDA device/runtime, CUBLAS, CUFFT, and CUSOLVER libraries

ArrayFire is a general-purpose library that simplifies the process of developing software that targets parallel and massively-parallel architectures i

PyCUDA lets you access Nvidia's CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist-so what's so special about P

gpustat Just less than nvidia-smi? NOTE: This works with NVIDIA Graphics Devices only, no AMD support as of now. Contributions are welcome! Self-Promo

CuPy : A NumPy-compatible array library accelerated by CUDA Website | Docs | Install Guide | Tutorial | Examples | API Reference | Forum CuPy is an im

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples

Stock Statistics/Indicators Calculation Helper VERSION: 0.3.2 Introduction Supply a wrapper StockDataFrame based on the pandas.DataFrame with inline s

Tensorflow 2 Object Detection API Bu tutorial, TensorFlow 2.x'in kararlı sürümü olan TensorFlow 2.3'ye yöneliktir. Bu, görüntülerde / videoda nesne a

Stock Statistics/Indicators Calculation Helper VERSION: 0.3.2 Introduction Supply a wrapper StockDataFrame based on the pandas.DataFrame with inline s

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

Karoo GP Karoo GP is an evolutionary algorithm, a genetic programming application suite written in Python which supports both symbolic regression and

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

pyjanitor pyjanitor is a Python implementation of the R package janitor, and provides a clean API for cleaning data. Why janitor? Originally a port of

pdpipe ˨ Easy pipelines for pandas DataFrames (learn how!). Website: https://pdpipe.github.io/pdpipe/ Documentation: https://pdpipe.github.io/pdpipe/d

What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular data

swifter A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner. Blog posts Release 1.0.0 Fir

Scale your pandas workflows by changing one line of code To use Modin, replace the pandas import: # import pandas as pd import modin.pandas as pd Inst

pandas API on Apache Spark Explore Koalas docs » Live notebook · Issues · Mailing list Help Thirsty Koalas Devastated by Recent Fires The Koalas proje

cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Built based on the Apache Arrow columnar memory format,

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great

Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

lazyprofiler Lazy Profiler is a simple utility to collect CPU, GPU, RAM and GPU Memory stats while the program is running. Installation Use the packag

In-depth EDA (target analysis, comparison, feature analysis, correlation) in two lines of code! Sweetviz is an open-source Python library that generat

PandasGUI A GUI for analyzing Pandas DataFrames. Demo Installation Install latest release from PyPi: pip install pandasgui Install directly from Githu

Pandas Profiling Documentation | Slack | Stack Overflow Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great