Laurae2

lgbdl

LightGBM Online Installer [ devtools::install_github("Laurae2/lgbdl") ]

LauraeDS

Laurae's Data Science R Package

LauraeCE

Laurae's Cross-Entropy Optimization for R

ez_xgb

Easy xgboost installation for R users (no recursive)

ml-perf

xgbdl

xgboost Online Installer [ devtools::install_github("Laurae2/xgbdl") ]

Laurae2

Laurae's Simplified R - The sequel of Laurae Package

LauraeCpp

Parallel R for HPC on a Single Computer using C++

R_Installation

Fully setting up and installing R in Windows / Debian / Ubuntu (Version: 3.5.1)

LauraeParallel

Laurae's Parallel Load Balancing for R

xgblgb_compare

Comparing xgboost and LightGBM: compiler, CPU pinning

R_benchmarking

Benchmarking R and C++ for Machine Learning Metrics

Cbc.jl

Interface to the Coin-OR Cbc solver for mixed-integer programming

docker-brew-clearlinux

Dockerhub image snapshots for Clear Linux

GBM-adv-workshop-Bp19

Advanced GBM Workshop - Budapest, Nov 2019

keras

R Interface to Keras

LightGBM

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

mallinfo

Memory allocation information from glibc

pbapply

:exclamation: This is a read-only mirror of the CRAN R package repository. pbapply — Adding Progress Bar to '*apply' Functions. Homepage: https://github.com/psolymos/pbapply Report bugs for this package: https://github.com/psolymos/pbapply/issues

PiBlynk

NodeJS and Python libraries for using Blynk APP on Raspberry Pi

pkgdown

Generate static html documentation for an R package

pygbm

Experimental Gradient Boosting Machines in Python with numba.

RInno

How to install local shiny apps

Rtsne

R wrapper for Van der Maaten's Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding

sapui5_walkthrough

SAPUI5 Walkthrough Tutorial Git Snapshot

stR

R's stR package without rgl nor X11 dependency

v8-3.14

v8-3.14 (without all the useless stuff from Git) for R

WindowsMT

R Windows Multithreading Package

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

xgboost-fast-hist-perf-lab

Deeper look into performance of tree_method='hist' for multi-core CPUs