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awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-r

A curated list of awesome R packages, frameworks and software.

bigdl

BigDL: Distributed Deep Learning Library for Apache Spark

biham-middleton-levine-traffic-model-simulation

Simulate BML Traffic Model using both C and R, plot and summary a BML grid

bindeps.jl

Tool for building binary dependencies for Julia modules

bitcoin

Bitcoin Core integration/staging tree

bml

Biham–Middleton–Levine traffic model

bml-cuda

CUDA-accelerated implementation of the Biham-Middleton-Levine traffic model

caffe

Caffe: a fast open framework for deep learning.

cmooc

cmu-multimodalsdk

CMU MultimodalSDK is a machine learning platform for development of advanced multimodal models as well as easily accessing and processing multimodal datasets.

community-detection-dynamic

communitydetection.jl

Community Detection in Julia

compose.jl

Declarative vector graphics

conjugatepriors.jl

A Julia package to support conjugate prior distributions.

corona_tscs

This is the data repository of the CoronaNet project on government responses to the COVID-19 pandemic and the data/code repository for the paper "A Retrospective Bayesian Model for Measuring Covariate Effects on Observed COVID-19 Test and Case Counts".

cpp.jl

Utilities for calling C++ from Julia

csclrec

Code repo for the EDM 2020 submission - CSCLRec: Personalized Recommendation of Forum Posts to Support Socio-collaborative Learning

cw2vec

Details of paper cw2vec

cxx.jl

The Julia C++ Interface

dataframes.jl

library for working with tabular data in Julia

deeplearningbook-chinese

Deep Learning Book Chinese Translation

dfa.jl

detrended fluctuation analysis

edudata

Edudata: Datasets in Education and convenient interface for downloading and preprocessing dataset in education

ensemble-models-majority-vote-fwls

A Python framework for building majority vote and feature weighted linear stacking (FWLS) ensemble models. As an example, ensemble models are built to classify flower species of the Iris dataset. The models in the ensembles are a support vector machine (SVM), random forest, and k nearest neighbor.

evolvegcn

Code for EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

evolvinggraphs.jl

Dynamic Graph Analysis Framework in Julia

fast-rcnn

Fast R-CNN

fun

just for fun

ggn

Gumbel Graph Network (GGN) : A General Deep Learning Framework for Network Reconstruction