Concept
Perceptron
Cours associés (31)
EE-411: Fundamentals of inference and learning
This is an introductory course in the theory of statistics, inference, and machine learning, with an emphasis on theoretical understanding & practical exercises. The course will combine, and alternat
MATH-412: Statistical machine learning
A course on statistical machine learning for supervised and unsupervised learning
MGT-448: Statistical inference and machine learning
This course aims to provide graduate students a thorough grounding in the methods, theory, mathematics and algorithms needed to do research and applications in machine learning. The course covers topi
MGT-418: Convex optimization
This course introduces the theory and application of modern convex optimization from an engineering perspective.
EE-556: Mathematics of data: from theory to computation
This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees
MATH-212: Analyse numérique et optimisation
L'étudiant apprendra à résoudre numériquement divers problèmes mathématiques. Les propriétés théoriques de ces
méthodes seront discutées.
CS-433: Machine learning
Machine learning methods are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and pr
CS-423: Distributed information systems
This course introduces the foundations of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems.
ME-390: Foundations of artificial intelligence
This course provides the students with 1) a set of theoretical concepts to understand the machine learning approach; and 2) a subset of the tools to use this approach for problems arising in mechanica