This will train the network using a batch size of 100 and a learning rate of 0.001. It will stop after training 50 epoches. During training, at each epoch, it will train the model on batches (one ...

Autoencoder + Denoising Autoencoder implementation using Tensorflow, tested on MNIST - Issues · spiglerg/Denoising_Autoencoder_MNIST_Tensorflow ...

Anomaly Detection on the MNIST Dataset The demo program creates and trains a 784-100-50-100-784 deep neural autoencoder using the Keras library. An autoencoder is a neural network that learns to ...