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awesome-machine-learning

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

caffe

Caffe: a fast framework for deep learning. For the most recent version checkout the dev branch. For the latest stable release checkout the master branch.

cxxnet

CXXNET, yet another neural network toolkit

deep-learning-with-tensorflow

Deep Learning with TensorFlow by Packt

deepbeliefbird

Using speech recognition approaches (Deep Belief Net) for analyzing birdsong

deeplearningtutorials

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

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.

deepmat

Matlab Code for Restricted/Deep Boltzmann Machines and Autoencoders

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

graphviz4matlab

Matlab interface to Graphviz graph layout package. Allows interactive editing of the resulting graphs.

kaldi

This is now the official location of the Kaldi project.

liquidstatemachine-csim

This is a repo for an attempt to rebuild the LSM from Neural Micro Circuits ( http://www.lsm.tugraz.at/index.html ) I have tried to contact the orignal authors with no luck. If your them or you know them please contact me. The reason for this project is for my thesis. I have some time series that I would love to try a liquid state machine on. The original project page says it works for windows. This was in about early 2002 with win xp. The site also says they dont offer windows support. So I would like to attempt a win 7 version and if that goes well perhaps keep updating the project for win 8 and beyond. What is a Liquid State Machine? It is a type of neural network that has a pool of neurons that has randomly selected neurons connected as inputs. An LSM also has randomly sampled neurons as outputs. LSMs are suppose to be good to time series data as they have a "memory". This memory is the small circuits created by random connections of the neurons in the liquid.

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

neuralnetworks

java deep learning algorithms and deep neural networks with gpu acceleration

pybrain

python-ant-colony-tsp-solver

Solves the TSP using multithreaded ACO method

python_speech_features

This library provides common speech features for ASR including MFCCs and filterbank energies.

rbm_toolbox

mostly changes in RBM code. including PCD

restricted-boltzmann-machines

Restricted Boltzmann Machines in Python.

speech_recog

Using Deep Belief Networks to convert agricultural speech data to text

spiking-neural-network

Pure python implementation of SNN

tensorflow-tutorials

Simple tutorials using Google's TensorFlow Framework