Concept
Régression logistique
Cours associés (39)
MATH-413: Statistics for data science
Statistics lies at the foundation of data science, providing a unifying theoretical and methodological backbone for the diverse tasks enountered in this emerging field. This course rigorously develops
BIO-322: Introduction to machine learning for bioengineers
Students understand basic concepts and methods of machine learning. They can describe them in mathematical terms and can apply them to data using a high-level programming language (julia/python/R).
EE-612: Fundamentals in statistical pattern recognition
This course provides in-depth understanding of the most fundamental algorithms in statistical pattern recognition or machine learning (including Deep Learning) as well as concrete tools (as Python sou
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
MATH-408: Regression methods
General graduate course on regression methods
PHYS-467: Machine learning for physicists
Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practi
MATH-236: Probability and statistics II
Linear statistical methods, analysis of experiments, logistic regression.
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
MATH-412: Statistical machine learning
A course on statistical machine learning for supervised and unsupervised learning
FIN-403: Econometrics
The course covers basic econometric models and methods that are routinely applied to obtain inference results in economic and financial applications.