Deep Learning Tutorials

Explore basic math concepts for data science and deep learning such as scalar and vector, determinant, singular value decomposition, and more.

In this tutorial to deep learning in R with RStudio's keras package, you'll learn how to build a Multi-Layer Perceptron (MLP).

Learn how to build a neural network and how to train, evaluate and optimize it with TensorFlow

In this tutorial, you'll get an overview of Artificial Intelligence (AI) and take a closer look in what makes Machine Learning (ML) and Deep Learning different.

In this tutorial, you'll learn about Tensors, PyTorch, and how to create a simple neural network with PyTorch.

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!