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Sixiang Hu's Projects

caffe icon caffe

Caffe: a fast open framework for deep learning.

dataman icon dataman

R package for data cleaning, preliminary data analysis and modeling assessing with visualisation.

invester icon invester

Assets forecast and Portfolio optimisation

lanyon-plus icon lanyon-plus

Based on lanyon - A content-first, sliding sidebar theme for Jekyll. Demo at

lightgbm icon 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.

minimal-mistakes icon minimal-mistakes

:triangular_ruler: A flexible two-column Jekyll theme. Perfect for personal sites, blogs, and portfolios hosted on GitHub or your own server.

rbokeh icon rbokeh

R interface to Bokeh http://hafen.github.io/rbokeh/

shinymlr icon shinymlr

shiny-mlr: Integration of the mlr package into shiny

simpleblog icon simpleblog

View blog here: http://brooksandrew.github.io/simpleblog

vlmcsd icon vlmcsd

KMS Emulator in C (currently runs on Linux including Android, FreeBSD, Solaris, Minix, Mac OS, iOS, Windows with or without Cygwin)

vowpal_wabbit icon vowpal_wabbit

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

xgboost icon 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

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