zhouxiazx's repositories
WordEmbeddingAutoencoder
An autoencoder to calculate word embeddings as mentioned in Lebret/Collobert paper 2015
Tweety
Markov Bot based on bigram probabilities to generate tweets from your tweet history.
PTVS
Python Tools for Visual Studio
EntitySentiment
Entity level sentiment analysis for product reviews using deep learning
azure-sdk-for-python
Microsoft Azure SDK for Python
awesome-bigdata
A curated list of awesome big data frameworks, ressources and other awesomeness.
py-must-watch
Must-watch videos about Python
DNN-HMM
This directory contains all the Perl scripts and MATLAB codes we writed for the identification of replication domains using DNN-HMM in our paper.
opencv
Open Source Computer Vision Library
cxxnet
fast, concise, distributed deep learning framework
rabit
Reliable Allreduce and Broadcast Interface for distributed machine learning
xgboost
Large-scale and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, on single node, hadoop yarn and more.
dmlc-core
A common code-base for Distributed Machine Learning in C++
minerva
Minerva: a fast and flexible tool for deep learning on multi-GPU. It provides ndarray programming interface, just like Numpy. Python bindings and C++ bindings are both available. The resulting code can be run on CPU or GPU. Multi-GPU support is very easy.
wormhole
Portable, Scalable and Reliable Distributed Machine Learning, support various platforms including Hadoop YARN, MPI, etc.
visionworkbench
The NASA Vision Workbench is a general purpose image processing and computer vision library developed by the Autonomous Systems and Robotics (ASR) Area in the Intelligent Systems Division at the NASA Ames Research Center.
go
The Open Source Data Science Masters
styleguide
Style guides for Google-originated open-source projects
hadoop2.6_Win_x64
Hadoop 2.6 distribution with hadoop.dll and winutils.exe . Add JAVA_HOME and HADOOP_HOME as env variables. Also add path to Hadoop2.6\bin and java\bin.
DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
gait-1
Gait analysis.
spark-distributed-louvain-modularity
Spark / graphX implementation of the distributed louvain modularity algorithm
ActionRecognition-2
Recognition of daily-life actions by machine learning
speech-router
A way to utilize Chrome's speech recognition APIs to perform actions when specific text is heard.
Metrics
Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave