Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

Deep Learning for humans

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

Implement the LeNet using tensorflow to recognize handwritten number. Training with MNIST.

卷积神经网络之LeNet-5实现 The LeNet-5 Implementation of Convolutional Neural Network

tensorflow-lenet5

BPNN, SVC, SVR, CART, GSOM, LOF, K_MEANS, GRNN, LR, MLR

Stock market prediction using GRNN

《统计学习方法》

NeuPy is a Tensorflow based python library for prototyping and building neural networks

How to do Unsupervised Clustering with Keras

C++ Implementation of the RBF (Radial Basis Function) Network and choosing centroids using K-Means++

This project is the same with deeplearning.net, but the comment is written for chinese

Classification of the Hyperspectral Image Indian Pines with Convolutional Neural Network

Stacked Denoising Autoencoders (SDA) implemented in TensorFlow to analyze clinical health records and construct deep learning models to predict future patient complications.

Implementation and improvement of paper 'Learning Multiple Views with Orthogonal Denoising Autoencoders'

sklearn wrappers for stacked denoising autoencoders

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

Machine learning software for rapid analysis of scientific spectra.

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Simple Implementation of AutoEncoder, one type of deep learning algorithm. This is implemented based on Tensorflow.

Savitzky Golay Filter Implementation in Python

LeNet-5 convolutional network with TensorFlow

PyTorch implementation of LeNet-5 with live visualization

Stock Market Prediction Using Neural Network Models (Backpropagation, RNN, RBF) Keras with Tensorflow backend

RBF layer for Keras

RBF Network using Theano, climin, and sklearn.