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hmm_speech_recognition_demo

A demo for simple isolated Chinese speech word recognition using GMMHMM in Python

hrrp_recognize

keras

Deep Learning for humans

keras---deep-auto-encoder-trained-layerwise

The project codes up a three hidden layer deep auto encoder, trained in a greedy layerwise fashion for initializing a corresponding deep neural network. Also, it consider training criteria such as dropout and sparsity for improving feature learning.

keras-temporal-autoencoder

Keras framework for autocovariance-based dimensionality reduction of time series data with deep neural networks.

keras-tutorials

Keras-Tutorials

keras_extensions

A collection of small extensions to Keras (RBM, momentum schedule, ..)

learning_identification_internode_dynamics

Development of a Bayesian learning framework for HSMM characterization of the wireless RF observations, with occupancy periods and each individual RF device being classified as distinct states in the HSMM.

libsdae-autoencoder-tensorflow

A simple Tensorflow based library for deep and/or denoising AutoEncoder.

machine-learning

Machine learning in C++ and MATLAB

machinelearning

机器学习

matdl

A lightweight MATLAB deeplearning toolbox,based on gpuArray.

matlab-bayesian-estimation

Matlab Toolbox for Bayesian Estimation

mlstm-fcn

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

nndl.github.io

《神经网络与深度学习》 Neural Network and Deep Learning

nnet

A small collection of neural network algorithms in Go (no longer maintained)

np-hmm

General Bayesian non-parametric hidden Markov model

paysage

Unsupervised learning and generative models in python/pytorch.

phd_thesis_markdown

Template for writing a PhD thesis in Markdown

probabilistic-models

Collection of probabilistic models and inference algorithms

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

pydeep

PyDeep is a machine learning / deep learning library with focus on unsupervised learning. The library has a modular design, is well documented and purely written in Python/Numpy. This allows you to understand, use, modify, and debug the code easily. Furthermore, its extensive use of unittests assures a high level of reliability and correctness.

pyhsmm

pyhsmm-library-models

library models built on top of pyhsmm

pyro

Deep universal probabilistic programming with Python and PyTorch

pyvb

Python implementation for Variational Bayesian Learning

radar-hrrp-dl

Radar HRRP classfication deep learning

rbm

RBM;Contrastive Divergence;Restricted Boltzmann Machine

rbm-1

Initial commit

rbm-dbn-theano-dl4j

Train a DBN to classify a set of test data similar to MNIST, Using DL4J & theano