This tutorial will give a short introduction to PyTorch basics, and get you setup for writing your own neural networks. This notebook is part of a lecture series on Deep...

GPU/TPU,UvA-DL-Course

In this tutorial, we will take a closer look at (popular) activation functions and investigate their effect on optimization properties in neural networks. Activation functions...

GPU/TPU,UvA-DL-Course

In this tutorial, we will review techniques for optimization and initialization of neural networks. When increasing the depth of neural networks, there are various challenges...

Image,Initialization,Optimizers,GPU/TPU,UvA-DL-Course

In this tutorial, we will implement and discuss variants of modern CNN architectures. There have been many different architectures been proposed over the past few years. Some...

Image,GPU/TPU,UvA-DL-Course

In this tutorial, we will discuss one of the most impactful architectures of the last 2 years: the Transformer model. Since the paper Attention Is All You Need by Vaswani et...

Text,GPU/TPU,UvA-DL-Course

In this tutorial, we will discuss the application of neural networks on graphs. Graph Neural Networks (GNNs) have recently gained increasing popularity in both applications...

Graph,GPU/TPU,UvA-DL-Course

In this tutorial, we will look at energy-based deep learning models, and focus on their application as generative models. Energy models have been a popular tool before the...

Image,GPU/TPU,UvA-DL-Course

In this tutorial, we will take a closer look at autoencoders (AE). Autoencoders are trained on encoding input data such as images into a smaller feature vector, and afterward,...

Image,GPU/TPU,UvA-DL-Course

In this tutorial, we will take a closer look at complex, deep normalizing flows. The most popular, current application of deep normalizing flows is to model datasets of...

Image,GPU/TPU,UvA-DL-Course

In this tutorial, we implement an autoregressive likelihood model for the task of image modeling. Autoregressive models are naturally strong generative models that constitute...

Image,GPU/TPU,UvA-DL-Course

In this tutorial, we will take a closer look at a recent new trend: Transformers for Computer Vision. Since [Alexey Dosovitskiy et...

Image,GPU/TPU,UvA-DL-Course

In this tutorial, we will discuss algorithms that learn models which can quickly adapt to new classes and/or tasks with few samples. This area of machine learning is called...

Few-shot-learning,MAML,ProtoNet,GPU/TPU,UvA-DL-Course

In this tutorial, we will take a closer look at self-supervised contrastive learning. Self-supervised learning, or also sometimes called unsupervised learning, describes the...

Image,Self-Supervised,Contrastive-Learning,GPU/TPU,UvA-DL-Course

In this tutorial we will show how to combine both Kornia and PyTorch Lightning to perform efficient data augmentation to train a simple model using the GPU in batch mode...

Image,GPU/TPU,Lightning-Examples

This notebook describes the self-supervised learning method Barlow Twins. Barlow Twins differs from other recently proposed algorithms as it doesn't fall under the category of...

Image,Self-Supervised,GPU/TPU,Lightning-Examples

How to train a GAN! Main takeaways: 1. Generator and discriminator are arbitrary PyTorch modules. 2. training_step does both the generator and discriminator training.

Image,GPU/TPU,Lightning-Examples

Train a Resnet to 94% accuracy on Cifar10!

Image,GPU/TPU,Lightning-Examples

This notebook will walk you through how to start using Datamodules. With the release of `pytorch-lightning` version 0.9.0, we have included a new class called...

GPU/TPU,Lightning-Examples

This notebook introduces the [Fine-Tuning Scheduler](https://finetuning-scheduler.readthedocs.io/en/stable/index.html) extension and demonstrates the use of it to fine-tune a...

Fine-Tuning,GPU/TPU,Lightning-Examples

In this notebook, we'll go over the basics of lightning by preparing models to train on the [MNIST Handwritten Digits dataset](https://en.wikipedia.org/wiki/MNIST_database).

Image,GPU/TPU,Lightning-Examples

In this notebook, we'll train a model on TPUs. Updating one Trainer flag is all you need for that. The most up to documentation related to TPU training can be found...

Image,GPU/TPU,Lightning-Examples

Main takeaways: 1. RL has the same flow as previous models we have seen, with a few additions 2. Handle unsupervised learning by using an IterableDataset where the dataset...

RL,GPU/TPU,Lightning-Examples

This notebook will use HuggingFace's `datasets` library to get data, which will be wrapped in a `LightningDataModule`. Then, we write a class to perform text classification on...

Text,GPU/TPU,Lightning-Examples

This is a template to show how to contribute a tutorial.

GPU/TPU,templates