NDAK15014U Advanced Topics in Machine Learning (ATML)

Volume 2015/2016
Content

The purpose of this course is to expose the student to selected advanced topics in machine learning. The course will bring the student up to a level sufficient for master thesis work within machine learning. 

Learning Outcome

Knowledge on

  • Selected advanced topics in machine learning, including:
    • design of learning algorithms
    • analysis of learning algorithms

The exact list of topics will depend on the teachers and trends in machine learning research. They will be announced on the course's Absalon website.

Skills to

  • Read and understand recent scientific literature in the field of machine learning
  • Apply the knowledge obtained by reading scientific papers
  • Compare machine learning methods and assess their potentials and shortcommings
     

Competences to

  • Understand advanced methods, and to transfer the gained knowledge to solutions to practical problems
  • Plan and carry out self-learning
     

See Absalon.

Passed the course “(Statistical Methods for) Machine Learning” or similar.
Lectures and class instructions.
  • Category
  • Hours
  • Class Instruction
  • 14
  • Exam Preparation
  • 20
  • Exercises
  • 74
  • Lectures
  • 28
  • Preparation
  • 70
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Continuous assessment
5-7 weekly take home exercises.
The final grade will be the average over all assignments except the worst one.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Re-exam

30 minutes oral exam in course curriculum, without preparation.
To be eligible for the re-exam, a student must have handed in all but at most two assignments, each demonstrating serious efforts to solve the assignment.

Criteria for exam assesment

To obtain the grade 12 the student must be able to:

1.    Document understanding of the assignments including the relevant literature and/or other materials needed for conducting the assignment.
2.    Document solutions to the assignment.
3.    Document any experiments made and any drawn conclusions.