Catégorie

Apprentissage automatique

Cours associés (32)

This course introduces the theory and application of modern convex optimization from an engineering perspective.

MGT-302: Introduction to data driven business analytics

This course focuses on methods and algorithms needed to apply machine learning with an emphasis on applications in business analytics

CIVIL-426: Machine learning for predictive maintenance applications

The course aims to develop machine learning algorithms capable of efficiently detecting faults in complex industrial and infrastructure assets, isolating their root causes, and ultimately predicting t

MATH-520: Topics in machine learning

Mathematical analysis of modern supervised machine learning techniques, from linear methods to artificial neural networks.

ENG-209: Data science for engineers with Python

Ce cours est divisé en deux partie. La première partie présente le langage Python et les différences notables entre Python et C++ (utilisé dans le cours précédent ICC). La seconde partie est une intro

CS-625: Transfer learning and meta-learning

This seminar course covers principles and recent advancements in machine learning methods that have the ability to solve multiple tasks and generalize to new domains in which training and test distrib

PHYS-754: Lecture series on scientific machine learning

This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way.

EE-559: Deep learning

This course explores how to design reliable discriminative and generative neural networks, the ethics of data acquisition and model deployment, as well as modern multi-modal models.

PHYS-512: Statistical physics of computation

The students understand tools from the statistical physics of disordered systems, and apply them to study computational and statistical problems in graph theory, discrete optimisation, inference and m

EE-735: Online learning in games

This course provides an overview of recent developments in online learning, game theory, and variational inequalities and their point of intersection with a focus on algorithmic development. The prima

MICRO-452: Basics of mobile robotics

The course teaches the basics of autonomous mobile robots. Both hardware (energy, locomotion, sensors) and software (signal processing, control, localization, trajectory planning, high-level control)

CS-421: Machine learning for behavioral data

Computer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will co