Course Overview

Machine learning is playing a fundamental role in our daily life from the way we check emails right down to the way we search online. This course will introduce a number of representative machine learning methods, and show how to utilize them to solve the ranking problem in the field of information retrieval.

Learning Achievement

(1) Be able to perform classification and regression using both linear and non-linear models;
(2) Be able to perform learning to rank based on both linear and non-linear models;

Competence

Course prerequisites

Grading Philosophy

Report(3times)

Course schedule

Guidance (introduction of tools and libraries for real implementation)
Classification-1 (linear model for classification)
Classification-2 (non-linear model for classification)
Classification-3 (classification based on PyTorch)
Regression-1 (linear model for regression)
Regression-2 (non-linear model for regression)
Regression-3 (regression based on PyTorch)
Ranking-1 (learning to rank)
Ranking-2 (learning to rank)
Ranking-3 (learning to rank based on PyTorch)

Course type

Lectures

Online Course Requirement

Instructor

Yu Haitao

Other information

Site for Inquiry

Link to the syllabus provided by the university