Kursöversikt
The purpose with this course is to give a thorough introduction to deep learning, also known as deep neural networks. Over the last few years, deep machine learning has dramatically changed the state of the art performance in various fields including speech-recognition, computer vision and reinforcement learning (used, e.g., to learn how to play Go). We focus initially on basic principles regarding how these networks are constructed and trained, we then move on to study the involved optimisation problems in more detail and finally we cover a range of more advanced topics including generative adversarial networks (GANs). The overall objective is to provide a solid understanding of how and why deep machine learning is useful, as well as the skills to apply them to solve problems of practical importance.
Kurssammanfattning:
Datum | Information | Sista inlämningsdatum |
---|---|---|
Tis den 28 mar 2023 | Quiz Quiz 1 | ska lämnas in senast 8.30 |
Quiz Quiz 2 | ska lämnas in senast 8.30 | |
Quiz Quiz 3 | ska lämnas in senast 8.30 | |
Fre den 21 apr 2023 | Uppgift Module 1 - Home assignment | ska lämnas in senast 19:00 |
Tis den 23 maj 2023 | Uppgift Module 2 - Project report | ska lämnas in senast 23.59 |
Fre den 26 maj 2023 | Uppgift Module 3 - Quiz on Discriminative Modeling and Uncertainty Estimation | ska lämnas in senast 17:00 |
Uppgift Module 3 - Quiz on Generative Models | ska lämnas in senast 17:00 | |
Fre den 2 jun 2023 | Uppgift Module 3 - Exercise on Generative Models 1 (VAE) | ska lämnas in senast 17:00 |
Uppgift Module 3 - Exercise on Generative Models 2 (GAN) | ska lämnas in senast 17:00 | |
Uppgift Module 3 - Exercise on Uncertainty Estimation 1 | ska lämnas in senast 17:00 | |
Uppgift Module 3 - Exercise on Uncertainty Estimation 2 | ska lämnas in senast 17:00 | |
Quiz Understanding mini-batch gradient descent (part 2) |