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A demo for simple isolated Chinese speech word recognition using GMMHMM in Python
Deep Learning for humans
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 framework for autocovariance-based dimensionality reduction of time series data with deep neural networks.
Keras-Tutorials
A collection of small extensions to Keras (RBM, momentum schedule, ..)
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.
A simple Tensorflow based library for deep and/or denoising AutoEncoder.
Machine learning in C++ and MATLAB
机器学习
A lightweight MATLAB deeplearning toolbox,based on gpuArray.
Matlab Toolbox for Bayesian Estimation
Multivariate LSTM Fully Convolutional Networks for Time Series Classification
《神经网络与深度学习》 Neural Network and Deep Learning
A small collection of neural network algorithms in Go (no longer maintained)
General Bayesian non-parametric hidden Markov model
Unsupervised learning and generative models in python/pytorch.
Template for writing a PhD thesis in Markdown
Collection of probabilistic models and inference algorithms
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 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.
library models built on top of pyhsmm
Deep universal probabilistic programming with Python and PyTorch
Python implementation for Variational Bayesian Learning
Radar HRRP classfication deep learning
RBM;Contrastive Divergence;Restricted Boltzmann Machine
Initial commit
Train a DBN to classify a set of test data similar to MNIST, Using DL4J & theano
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.