Introduction to Neural Networks with PyTorch

Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.

• Course Introduction
• Meet your instructors, get a short overview of what you'll be learning, check your prerequisites, and learn how to use the workspaces and notebooks found throughout the lessons.
• Introduction to Neural Networks
• In this lesson, Luis will give you solid foundations on deep learning and neural networks. You'll also implement gradient descent and backpropagation in Python right here in the classroom.
• Implementing Gradient Descent
• Mat will introduce you to a different error function and guide you through implementing gradient descent using numpy matrix multiplication.
• Training Neural Networks
• Now that you know what neural networks are, in this lesson you will learn several techniques to improve their training.
• Deep Learning with PyTorch
• Learn how to use PyTorch for building deep learning models.
• Create Your Own Image Classifier
• In this project, you'll create your own image classifier and then train—and evaluate its performance—using one of the most classic and well-studied computer vision data sets, CIFAR-10.