Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences (NIPS 2016) - Tensorflow 1.0

Predict handwritten digits with CoreML

End to End learning for Video Generation from Text

🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

Pytorch mnist example

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

Tensorflow implementation for 'LCNN: Lookup-based Convolutional Neural Network'. Predict Faster using Models Trained Fast with Multi-GPUs

Official adversarial mixup resynthesis repository

Draw and classify digits (0-9) in a browser using machine learning

TensorFlow implementation of "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection"

Convolutional neural networks with Python 3

Implementation of GANomaly with MNIST dataset

Attention mechanism with MNIST dataset

PyTorch implementation of "Reconstruction by inpainting for visual anomaly detection (RIAD)"

Implementation of MNIST dataset for handwriting recognition.

Recognize handwritten digits using back-propagation algorithm on MNIST data-set

TensorFlow implementation of "Selective Kernel Networks"

It is a Python GUI in which you can draw a digit and the ML Algorithm will recognize what digit it is. We have used Mnist dataset

RNN classifier built with Keras to classify MNIST dataset