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espresso

Speeding up and debittering Caffe by adding Halide

expressgnn

facedetection_cnn

Multi-view Face Detection Using Deep Convolutional Neural Networks

faster_rcnn

Faster R-CNN

fb-caffe-exts

Some handy utility libraries and tools for the Caffe deep learning framework.

fido

A lightweight C++ machine learning library for embedded electronics and robotics.

fitml

A collection of python Machine Learning articles and examples. You will find code related to Reinforcement Learning, Q Learning, MDP, Bellman, OpenAI solutions and others. You can watch our agents here http://bit.ly/2Ayj4vA

fuel

A data pipeline framework for machine learning

ga3c

Hybrid CPU/GPU implementation of the A3C algorithm for deep reinforcement learning.

gemmlowp

Low-precision matrix multiplication

general_deep_q_rl

General deep reinforcement learning framework

generative-adversial

image generation via GANs

groundhog

Library for implementing RNNs with Theano

gsn

Efficient implementation of Generative Stochastic Networks

h-dqn

Reproduction of Kulkarni et al. (2016) in Python

hierarchical_il_rl

Code for hierarchical imitation learning and reinforcement learning

honeybadgerbft-python

The Honey Badger of BFT Protocols

horovod

Distributed training framework for TensorFlow.

hound

Lightning fast code searching made easy

ift6266h15

repo for IFT6266 course projects & assignments

image_classification

An implementation (in R) of a not so usual "deep learning" architecture using K-Means and SVM

imagenet-training

ImageNet training using torch

imagenet-validation.torch

Fast and easy testing of imagenet models

inception

infogan

is13

RNN and Spoken Language Understanding

is_that_a_duplicate_quora_question

jumphash

Really remarkably trivial node bindings for Google's jump consistent hash.

kaggle-cifar10-torch7

Code for Kaggle-CIFAR10 competition.

kaldi-lstm

C++ implementation of LSTM (Long Short Term Memory), in Kaldi's nnet1 framework. Used for automatic speech recognition, possibly language modeling etc, the training can be switched between CPU and GPU(CUDA).