wqren,github

cracking-the-coding-interview

Solutions for the book: Cracking the coding interview V4. Written in C++.

GPU-accelerated LIBSVM is a modification of the original LIBSVM that exploits the CUDA framework to significantly reduce processing time while producing identical results. The functionality and interface of LIBSVM remains the same. The modifications were done in the kernel computation, that is now performed using the GPU.

cukmeans.py

Implementation of the kmeans algorithm using pycuda

cvac

The Computer Vision Algorithm Collection

cvconvnet

Convolution neural network library, based off http://conv-net.sourceforge.net/

datafu

Hadoop library for large-scale data processing

dbm

A generic implementation of a Deep Boltzmann Machine (without pretraining)

dbntoolbox

deep belief network toolbox written in Matlab, including algorithms of unsupervised feature learning, deep learning, and general machine learning

dc-ign

The Deep Convolutional Inverse Graphics Network

decaf-release

http://decaf.berkeleyvision.org/

deep-convolutional-network-on-fpga

a simplified version of LeNet5

deep-learning-scene-recognition

Using convolutional deep belief nets to learn natural scene representations

deep-pink

Deep Pink is a chess AI that learns to play chess using deep learning.

deep-recurrent-attentive-writer

Deep Recurrent Attentive Writer

deep_nets_iclr04

deep_q_rl

Theano-based implementation of Deep Q-learning

deeplearning

Code to build MLP models for outdoor head orientation tracking

deeplearning-class-2011

Code for Deep Learning class at Google

deeplearningtutorials

Deep Learning Tutorial notes and code. See the wiki for more info.

deeplearntoolbox

Matlab 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.