Deep learning‑tutorials

There is an optimal number of hidden layers and neurons for an artificial neural network (ANN). This tutorial discusses a simple approach for determining the optimal numbers for layers and neurons for ANN's.

In this tutorial, you’ll implement a medical imaging using deep learning paper with Python in Keras.

In this tutorial, you will learn & understand how to use autoencoder as a classifier in Python with Keras. You'll be using Fashion-MNIST dataset as an example.

In this tutorial, you'll learn & understand how to read nifti format brain magnetic resonance imaging (MRI) images, reconstructing them using convolutional autoencoder.

In this tutorial, you will learn and understand how to read jpeg format fingerprint images, reconstructing them using convolutional autoencoder.

Visualize the training parameters, metrics, hyperparameters or any statistics of your neural network with TensorBoard!

Learn what Generative Adversarial Networks are without going into the details of the math and code a simple GAN that can create digits!

In this tutorial, you'll learn more about autoencoders and how to build convolutional and denoising autoencoders with the notMNIST dataset in Keras.

In this tutorial, you’ll learn how to implement Convolutional Neural Networks (CNNs) in Python with Keras, and how to overcome overfitting with dropout.

This step-by-step tutorial will show you how to set up and use Jupyter Notebook on Amazon Web Services (AWS) EC2 GPU for deep learning.