Johns Hopkins Machine Learning 601.475 Fall 2020

Section 1
Schedule: Mon/Wed 1:30-2:45pm
Location: Online Only
Instructor: Prof. Mark Dredze
Recitation (optional): Fri 1:30-2:45pm

Section 2
Schedule: Mon/Wed 3:00-4:15pm
Location: Online Only
Instructor: Prof. Zach Wood-Doughty
Recitation (optional): Fri 1:30-2:45pm (joint with section 01)

Contact email:

This course is very popular, and interest exceeds space every semester. Therefore, the course has a strict enrollment limit and spots that become available when students drop will be given to students on the waitlist.

Enrollment is initially restricted to Computer Science and Robotics students only. Students from other departments are able to register after these students have finished registration. Each semester, many students drop the class and make room for those on the waitlist. While not everyone gets into the class, many do.

Pleaes do not email me asking to enroll in the class. If the course is full, add yourself to the waitlist and come to class on the first day.

Students who cannot register are welcome to attend lectures. Additionally, the course is offered every semester.



Websites for the class


This course takes an application driven approach to current topics in machine learning. The course covers supervised learning, unsupervised learning, semi-supervised learning, and several other learning settings. We will cover popular algorithms and will focus on how statistical learning algorithms are applied to real world applications. Students will implement several learning algorithms throughout the semester. The goal of this course is to provide students with the basic tools they need to approach various applications, such as:
  • Biology/Bioinformatics
  • Information Retrieval
  • Natural Language Processing
  • Speech Processing
  • Vision
We will focus on fundamental methods applicable to all applications. Application specific techniques, such as feature extraction, will be covered only to the benefit of understanding the basic methods.

Previous Years