Deep Learning Tutorials

Build a machine learning model for predicting the publisher’s name from an article using various Google Cloud technologies.

In this tutorial, you'll learn how to implement power applications like Prisma using TensorFlow 2.0.

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

Learn the basics of deep learning and neural networks along with some fundamental concepts and terminologies used in deep learning.

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.