hussien Goto Github PK

python-parallel-programming-cookbook-second-edition

Python Parallel Programming Cookbook – Second Edition, published by Packt

pytorch-biggraph

Generate embeddings from large-scale graph-structured data.

pytorch-cifar

95.47% on CIFAR10 with PyTorch

pytorch_geometric

Graph Neural Network Library for PyTorch

queens

The queens problem. Solves any number of chess queens problem using three different approaches: Combinatory: O(n^n) → slowest Permutations: O(n!) Tree optimized < O(n!) → fastest Generation is performed multi threaded, so all cores of CPU are used, for very large number of queens the ‘stop when found [n] solutions or more’ can be used, (0=all solutions) Results can be saved to a text file or copied to clipboard (total or selection), board image can also be copied as an image. Selected results can be transformed by translation, rotation or mirroring. Window geometry, n queens, stop solutions and dock positions are stored in main settings. It has been tested for n=34, providing the first solution in about 3 minutes on an 8 core i7 CPU.

research.lpca

This project analyzes the results of various models for Link Prediction on Knowledge Graphs using Knowledge Graph Embeddings. It allows to replicate the results in our work "Knowledge Graph Embeddings for Link Prediction: A Comparative Analysis" (https://arxiv.org/abs/2002.00819). Principal contributor: ANDREA ROSSI (https://github.com/AndRossi)

rgcn

Pytorch implementation of a RGCN Link Prediction Model

schemaorg

Schema.org - schemas and supporting software

scihub2pdf

Downloads pdfs via a DOI number, article title or a bibtex file, using the database of libgen(sci-hub) , arxiv

seal_ogb

An open-source implementation of SEAL for link prediction in open graph benchmark (OGB) datasets.

shadow_gnn

NeurIPS 2021: Improve the GNN expressivity and scalability by decoupling the depth and receptive field of state-of-the-art GNN architectures

soa11g_examples

Oracle SOA Suite 11g Examples

soen6441_youtubeanalyzerproject

spagobi-v4x

GitHub clone of SVN repo svn://svn.forge.objectweb.org/svnroot/spagobi/V_4.x/Server/trunk (cloned by http://svn2github.com/). This repo is not updated anymore. Please read at http://piotr.gabryjeluk.pl/blog:svn2github-problems

spark-mlib

experimental spark machine learning application

spark_course

sparkgpu

GPU* or SPARK* branches are used for generating GPU code in Tungsten/concact:@kiszk, MLlib branch is used for CUDA-MLlib project/concact:@bherta

spasql-utility-showcase-queries

Collection of combined SQL and SPARQL queries that address practical data access and manipulation challenges

springin28minutes

Spring Tutorial For Beginners

stacked-lstm-for-covid-19-outbreak-prediction

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, resulting in an ongoing pandemic. Long Short Term Memories(LSTMs) can solve numerous tasks not solvable by previous learning algorithms for recurrent neural networks (RNNs). LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition and anomaly detection in network traffic or IDS's (intrusion detection systems). LSTMs can also be efficiently applied for time-series predictions. In this project, its shows a four stacked LSTM network for early prediction new Coronavirus dissease infections in some of the mentioned affected countries (India, USA, Czech Republic and Russia) , which is based on real world data sets which are analyzed using various perspectives like day-wise number of confirmed cases, number of Cured cases, death cases. This attempt has been done to help the concerned authorities to get some early insights into the probable devastation likely to be effected by the deadly pandemic.

stanford-machine-learning-assignments

assignments of Machine Learning at Coursera

stare

EMNLP 2020: Message Passing for Hyper-Relational Knowledge Graphs

stellargraph

StellarGraph - Machine Learning on Graphs

strads

Parallel ML System - STRADS scheduler

the-free-hive-book

A free electronic book about Apache Hive. The book is geared towards SQL-knowledgeable business users with some advanced tips for devops.

torch-rgcn

A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).

videojs-youtube

YouTube playback technology for Video.js

virtualhome

API to run VirtualHome, a Multi-Agent Household Simulator

webextensions-examples

Example Firefox add-ons created using the WebExtensions API

wuzzuf_dataset_analysis_python