Machine Learning 1 (Winter Term 2019/2020)

Overview

Block course consisting of lectures and exercises (2/2/0)
List of modules
Lecturer: Bjoern Andres
Assistant: Holger Heidrich, Benedikt Jordan

Examination

Format
- Individual remote oral examinations about the contents of this course are offered for all participating students of all degree programmes.
- There will not be any written examination on the contents of this course in the Summer Term 2020.
Creditability
- Regulations regarding the creditability of the results of the examination depend on the degree programme and module. Regulations we are aware of are summarized below. Students in doubt are asked to check with the coordinator of their degree programme.
- CMS-*. In the degree programme Computational Modeling and Simulation (CMS), the individual remote oral examination replaces the written examination.
Scheduling open from 2020-06-18 through 2020-06-28
- Appointments for individual remote oral examinations are available now and can be scheduled exclusively through OPAL.
Registration open through 2020-07-03 (all forms need to be submitted by then)
- Only scheduled examinations can be registered.
- Students enrolled in the degree programme Computational Modeling and Simulation (CMS) need to
  - register their scheduled examination via SELMA
  - send the filled in and signed form Declaration of consent to an alternative form of an immaterial/oral examination to mlcv-exams@tu-dresden.de.
- Students enrolled in other degree programmes of the Faculty of Computer Science
  - who wish to credit the course toward one of the modules INF-BAS-*, INF-VERT-*, INF-VMI-* or INF-E-* need to
    - follow these instructions by the examination office of the faculty until 2020-07-03
    - send the filled in and signed form Declaration of consent to an alternative form of an immaterial/oral examination to mlcv-exams@tu-dresden.de.
  - who wish to credit the course toward any other module need to send to mlcv-exams@tu-dresden.de:
    - The filled in and signed registration form of the module toward which the course is to be credited. Respective forms are provided by the Examination Office and by the Service Center for International Students
    - The filled in and signed form Declaration of consent to an alternative form of an immaterial/oral examination
- Students enrolled in degree programmes of other faculties of TU Dresden need to email to mlcv-exams@tu-dresden.de:
  - Registration documents issued by the faculty of their degree programme, in case such documents exist
  - In case such documents do not exist: An informal request of a course certificate, including full name, matriculation number, degree programme, course title and email address to be used for correspondence
  - The filled in and signed form Declaration of consent to an alternative form of an immaterial/oral examination.

Lectures

Lecture Notes
Dates

2020-03-03, 9:20-12:40 (ZEU/160/H)
2020-03-04, 9:20-12:40 (ZEU/160/H)
2020-03-05, 9:20-12:40 (ZEU/160/H)
2020-03-06, 9:20-12:40 (ZEU/160/H)
2020-03-09, 7:30-10:50 (TOE/317)
2020-03-10, 7:30-10:50 (TOE/317)
2020-03-11, 7:30-9:00 (TOE/317)
2020-03-12, 7:30-9:00 (MOL/213)
2020-03-13, 7:30-9:00 (TOE/317)

Exercises

Exercises in APB-E065, in two groups (Group A from 1pm; group B from 2:50pm)
- 2020-03-04
- 2020-03-06
- 2020-03-10
- 2020-03-11
- 2020-03-13
Environment for programming tasks: python, scikit-learn, keras, tensorflow and/or corresponding C++ environment.
Assignments:
- 2020-03-04: Probability Theory
  A few slides of Sam Roweis will be used for introductory discussion in the exercise.
  Dimas prob. slides also used for introductory discussion in the exercise.
- 2020-03-04 and 2020-03-06: more Probability and SAT proofs
  Your questions; discuss problem 1.1.; Explain DGMs; discuss problems 2.1. and 2.2. and DGM in lecture notes; discuss problems 1.2.-5.;
  next to come: remaining proofs in exercise 2 and Classification
  starting code to read Data3: perceptron_task.py
- 2020-03-10: Your questions; Explain InfoGain, Gini; discuss problems 3.1. and 3.2.;
- 2020-03-11: Your questions; explain perceptron; discuss problems 3.3.-3.5.; send me your solutions for problem 2.3.b (to mlcv, subject "ML1, problem 2.3.b";
- 2020-03-13: Your questions; clustering; ordering with Python Script to read and transform the data
  corresponding solutions: ordering with Python Script

Related Literature

Machine Learning Textbooks