Content owner

Tampere University

Extent

5 cr

Course dates

7/3/2022 - 29/4/2022

Application period

24/1/2022 - 14/2/2022

Fees

75.00 € (15 €/cr)

Campus

Hervanta Campus

City

Tampere

Faculty or School

Faculty of Information Technology and Communication Sciences

Language of instruction

English

Code

DATA.ML.200

Study fields

Technology and Natural Sciences

Mode of study

Contact teaching

Study level

Advanced studies

Pattern Recognition and Machine Learning, 5, cr

Code: DATA.ML.200

Language of instruction: English

Description

Contents

Core content

Statistical Signal Processing: Estimation theory; Maximum likelihood; Estimation of signal parameters (e.g., phase, amplitude and frequency).
Detection theory; Receiver Operating Characteristics; Neyman-Pearson decision rule and relation to machine learning.
Linear models: regression and classification, support vector machines, logistic regression, regularization.
Modern tools: Random forests, Bagging, Boosting, Stacking, Deep Learning
Performance evaluation, cross-validation, bootstrapping
Implementations in Python: 1) Scikit-learn, 2) Keras

Course dates

Common

Lecture: / Demo lecture

07.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
09.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
11.03.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
14.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
16.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
18.03.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
21.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
23.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
25.03.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
28.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
30.03.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
01.04.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
04.04.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
06.04.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
08.04.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
11.04.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
20.04.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
22.04.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
25.04.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
27.04.2022 10:00 - 12:00, TAU Tietotalo TB103 auditorio (237)
29.04.2022 11:00 - 12:00, TAU Tietotalo TB103 auditorio (237)

Groups

Group 1: Exercise group 1

07.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
14.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
21.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
28.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
04.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
11.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
25.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)

Group 2: Exercise group 2

08.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
15.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
22.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
29.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
05.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
12.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
26.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)

Group 3: Exercise group 3

09.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
16.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
23.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
30.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
06.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
20.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
27.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)

Group 4: Exercise group 4

10.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
17.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
24.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
31.03.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
07.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
21.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)
28.04.2022 12:00 - 14:00, TAU Tietotalo TC217 tietokoneluokka (16)

Group 5: Exercise group 5

11.03.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)
18.03.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)
25.03.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)
01.04.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)
08.04.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)
22.04.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)
29.04.2022 10:00 - 12:00, TAU Tietotalo TC217 tietokoneluokka (16)

Prerequisites

The students are assumed to have the basic skills in probability, matrices and programming. Also the fundamentals of ML theory (SGN-13000 or SGN-13006) is strongly recommended.
Prerequisite

Code: SGN-13006
Name: Introduction to Pattern Recognition and Machine Learning
ECTS credits: 5
Mandatory: Mandatory
Alternativity: Either SGN-13000 or SGN-13006 is a prerequisite.

Compulsory Prerequisites

Introduction to Pattern Recognition and Machine Learning, DATA.ML.100, 5 cr

Teaching material

Assessment methods

Contact information

How to apply

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Pattern Recognition and Machine Learning, Lectures

Extent

Course dates

Application period

Fees

Campus

City

Faculty or School

Language of instruction

Code

Study fields

Mode of study

Study level

Common

Lecture: / Demo lecture

Groups

Group 1: Exercise group 1

Group 2: Exercise group 2

Group 3: Exercise group 3

Group 4: Exercise group 4

Group 5: Exercise group 5

Prerequisites

Compulsory Prerequisites

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Pattern Recognition and Machine Learning, Lectures

Extent

Course dates

Application period

Fees

Campus

City

Faculty or School

Language of instruction

Code

Study fields

Mode of study

Study level