Neural network - My Site

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Neural Networks

Teacher:  Fabian Aguirre

E-mail:
ECTS: 2.5
Evaluation: final exam
Previsional Place and time: 18 hours

Prerequisites:
Aim of the course:
Syllabus:
This course will introduce the student to some of the state of the art applications of neural networks. It will do so in a self-contained way. Starting from perceptrons, multi-layer perceptrons, and deep learning, it will cover all the way to diffusion and large language models. We will discuss the main ideas behind generative AI, both for image and text generation.

The intention is for the student to develop a working understanding and useful intuition of the most recent applications of neural networks. Familiarity with statistical learning and machine learning is preferred but not mandatory. Undergraduate knowledge of calculus, linear algebra, and probability is the only prerequisite.