Corso Deep Learning e Computer Vision con PyTorch
Course Description
Deep Learning course with application on Computer Vision, using the PyTorch Library.
Academic Year
2023-2024
The course will start on January 8th 2024.
Course objectives and outcomes
Objectives: to provide students with the fundamental elements of deep learning, demonstrate its application to computer vision, and form practical skills in implementing and using deep-learning-based systems.
Outcome: An understanding of fundamental concepts and methods of deep learning and its applications, focusing on computer vision, paired with a set of tools and skills required for realizing functioning deep-learning systems.
Required skills
The course will also give the basis to understand the fundamental concepts of machine learning, so knowing them is recommended but optional.
Course Outline
- Introduction to Machine Learning and Deep Learning (1 hour)
- Machine Learning Foundations (3 hours)
- Data Representation with Tensors (3 hours)
- Learning from Tensors: Gradient Descent and Backpropagation (4 hours)
- Designing and Improving Deep-learning Models for classification (3 hours)
- Real-Time Object Detection with YOLO (3 hours)
- Running Scientific Experiments with PyTorch (3 hours)
Course Assessment
The students can decide to take the exam in one of the following two formats (either one or the other):
1 CFU - written examination
2 CFU - development of a project in teams (max 3 people in each group)