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| Section for Cognitive Systems |
| DTU Compute |
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02450 Introduction to Machine Learning and Data Mining
Morten Mørup
Tue Herlau
Mikkel N. Schmidt
Maxim Khomiakov
Sayantan Sengupta
Ahmet Baglan
Martin Jørgensen
Jakob Thorsbro
Malte Jensen
Lorenzo Belgrano
Jonas Sonn Jørgensen
Alessandro Catania
Aksel Sylvest Obdrup
Sebastian Daugaard
Sara Nielsen
Machine learning and data mining
The course is designed around a data modeling framework shown in the figure.
Each lecture/assignment will focus on an aspect of the data modeling
framework.
We emphasize the holistic view of modeling in order to
motivate and stress the relevance of individual components and
building blocks, disseminate the obtained competence (see the
course learning
obejctives), and make them applicable for a broad spectrum of
engineering problems in e.g. biomedical engineering, chemistry,
electrical engineering, and informatics.
Resources
Lectures
The lectures will take place in building 303A auditorium 42 and 41 Tuesdays from 13:00-15:00.
Exercises
Exercises will take place after lectures Tuesdays from 15:00-17:00. Please bring a laptop computer for the exercises.
The exercises will be available in Matlab, R, and Python and we recommend selecting a language you are familiar with.
If you are unfamiliar with any of the languages, we recommend Matlab. The exercise rooms are:
- building 303A, auditorium 42, (Python):
-
"Sayantan Sengupta": says@dtu.dk; "Jakob Thorsbro": s134265@student.dtu.dk; "Maxim Khomiakov": maxk@dtu.dk
- building 303A, auditorium 41, (Python):
-
"Alessandro Catania": s171842@student.dtu.dk; "Jonas Sonn Jørgensen": s162886@student.dtu.dk; "Ahmet Baglan": s171787@student.dtu.dk
- building 308, student area on 1st floor (north), (Python):
-
"Sebastian Daugaard": s173082@student.dtu.dk
- building 308, student area on 1st floor (south), (Python+Matlab):
-
"Lorenzo Belgrano": s161174@student.dtu.dk
- building 308, room 101, (Python):
-
"Aksel Sylvest Obdrup": s144089@student.dtu.dk
- building 308, room 109, (Matlab):
-
"Sara Nielsen": s153173@student.dtu.dk
- building 308, room 117, (R):
-
"Martin Jørgensen": marjor@dtu.dk
- building 308, room 127, (Matlab):
-
"Malte Jensen": s153962@student.dtu.dk
Reading material, lecture slides and exercises
The course will use lecture notes and other freely available material. Lecture notes, slides, course assignment instructions etc. is available at the DTU Campusnet course page (requires formal enrolment to the course).
Course description
A description of the course can be found at the DTU Coursebase
Online help and support
Online help and support is available through the Piazza course platform.
Teachers
- Morten Mørup (MM), mmor@dtu.dk
- Tue Herlau (TH), tuhe@dtu.dk
Lecture schedule
| No. |
Date |
|
Subject |
Reading |
Homework |
| 1 | 4 September, 2018
| TH | Introduction
|
C1 |
|
| Data: Feature extraction, and visualization |
|---|
| 2 | 11 September, 2018
| TH | Data and feature extraction
|
C2, C3 | P3.1, P2.1, P3.2
|
| 3 | 18 September, 2018
| TH | Measures of similarity and summary statistics
|
C4 | P4.1, P4.2, P4.3
|
| 4 | 25 September, 2018
| TH | Data Visualization and probability
|
C5, C6 | P5.1, P5.2, P6.1
|
| Supervised learning: Classification and regression |
|---|
| 5 | 2 October, 2018
| TH | Decision trees and linear regression
(Project 1 due before 13:00) |
C7, C8 | P8.1, P7.1, P7.2
|
| 6 | 9 October, 2018
| TH | Overfitting and performance evaluation
|
C9 | P9.1, P9.2, P9.3
|
| | | Holiday | | |
| 7 | 23 October, 2018
| TH | Nearest Neighbor, Bayes and Naive Bayes
|
C10, C11 | P11.1, P11.2, P10.1
|
| 8 | 30 October, 2018
| TH | Artificial Neural Networks and Bias/Variance
|
C12, C13 | P13.1, P13.2, P13.3
|
| 9 | 6 November, 2018
| TH | AUC and ensemble methods
|
C14, C15 | P14.1, P14.2, P15.1
|
| Unsupervised learning: Clustering and density estimation |
|---|
| 10 | 13 November, 2018
| TH | K-means and hierarchical clustering
(Project 2 due before 13:00) |
C16 | P16.1, P16.2, P16.3
|
| 11 | 20 November, 2018
| TH | Mixture models and density estimation
|
C17, C18 | P18.1, P17.1, P17.2
|
| 12 | 27 November, 2018
| TH | Association mining
|
C19 | P19.1, P16.2, P16.3
|
| Recap |
|---|
| 13 | 4 December, 2018
| TH | Recap and discussion of the exam
(Project 3 due before 13:00) |
C1-C19 |
|
(Cx refers to Chapter x of the course notes. Px.y refers to problem number y in chapter x of the course notes.
The first listed problem will be that weeks discussion question at the exercises.)
