Machine Learning for Time Series 2021/2022 /CoursesID:2725

Detailed information

Keywords: deep learning machine learning time series

Most recent entry on 2022-01-18 

Lecturer

Dario Zanca

Organisational Unit

Friedrich-Alexander-Universität Erlangen-Nürnberg

Recording type

Vorlesungsreihe

Via

IdM-login / Studon

Language

English

These lectures convey concepts of machine learning especially with regard to time series applications. This is a specialisation course, the successful completion of "IntroPR", "Pattern Recognition" and/or "Pattern Analysis" is recommended. 

The following topics are covered in the lesson:

  • An overview of the application areas of time series analysis
  • Methodological foundations of machine learning (ML) for time series analysis
  • Design, implementation and evaluation of ML methods for dealing with time series problems

Course chapters

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Organizational information
Prof. Dr. Björn Eskofier
2021-10-19
IdM-login / Studon
00:10:05
2
Motivations and real world applications
Prof. Dr. Björn Eskofier
2021-10-19
IdM-login / Studon
00:15:02
3
Definitions and basic properties
Prof. Dr. Björn Eskofier
2021-10-19
IdM-login / Studon
00:18:34
4
i.i.d. property and the central limit theorem
Dario Zanca
2021-10-19
IdM-login / Studon
00:09:15
5
Recap
Dario Zanca
2021-10-19
IdM-login / Studon
00:02:09
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Lecture introduction
Dario Zanca
2021-10-26
IdM-login / Studon
00:02:28
2
Types of Machine Learning
Dario Zanca
2021-10-26
IdM-login / Studon
00:29:40
3
ML Pipeline and good practices
Dario Zanca
2021-10-26
IdM-login / Studon
00:26:11
4
Common ML Tasks with time series
Dario Zanca
2021-10-26
IdM-login / Studon
00:13:00
5
Linear regression for time series forecasting
Dario Zanca
2021-10-26
IdM-login / Studon
00:08:04
6
Recap
Dario Zanca
2021-10-26
IdM-login / Studon
00:02:04
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Bayes theorem
Dr. Luis Ignacio Lopera Gonzalez
2021-11-02
IdM-login / Studon
00:15:04
2
Model selection
Dr. Luis Ignacio Lopera Gonzalez
2021-11-02
IdM-login / Studon
00:06:53
3
Prior distributions
Dr. Luis Ignacio Lopera Gonzalez
2021-11-02
IdM-login / Studon
00:14:36
4
Bayesian linear regression
Prof. Dr. Oliver Amft
2021-11-02
IdM-login / Studon
00:19:45
5
Bayesian linear regression posterior
Prof. Dr. Oliver Amft
2021-11-02
IdM-login / Studon
00:13:52
6
Recap
Dr. Luis Ignacio Lopera Gonzalez
2021-11-02
IdM-login / Studon
00:03:13
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Bayesian inference for Gaussian processes
Dr. Luis Ignacio Lopera Gonzalez
2021-11-09
IdM-login / Studon
00:07:16
2
Gaussian processes introduction
Prof. Dr. Oliver Amft
2021-11-09
IdM-login / Studon
00:19:52
3
Gaussian processes regression
Prof. Dr. Oliver Amft
2021-11-09
IdM-login / Studon
00:17:42
4
Gaussian processes additivity
Prof. Dr. Oliver Amft
2021-11-09
IdM-login / Studon
00:17:06
5
Real world example
Dr. Luis Ignacio Lopera Gonzalez
2021-11-09
IdM-login / Studon
00:09:03
6
References
Dr. Luis Ignacio Lopera Gonzalez
2021-11-09
IdM-login / Studon
00:00:30
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Dr. Luis Ignacio Lopera Gonzalez
2021-11-16
IdM-login / Studon
00:01:15
2
GPC approach
Prof. Dr. Oliver Amft
2021-11-16
IdM-login / Studon
00:14:59
3
GPC prediction
Prof. Dr. Oliver Amft
2021-11-16
IdM-login / Studon
00:11:13
4
Laplace approximation
Dr. Luis Ignacio Lopera Gonzalez
2021-11-16
IdM-login / Studon
00:14:29
5
Expectation propagation approximation
Dr. Luis Ignacio Lopera Gonzalez
2021-11-16
IdM-login / Studon
00:16:43
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:01:22
2
State space models
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:11:18
3
Kalman filter
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:13:20
4
Kalman filter - An example and algorithmic view
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:09:38
5
Extended Kalman filter
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:16:04
6
Unscented Kalman filter
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:13:07
7
Critical comparison and recap
Prof. Dr. Björn Eskofier
2021-11-23
IdM-login / Studon
00:04:49
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Prof. Dr. Björn Eskofier
2021-11-30
IdM-login / Studon
00:03:46
2
Monte Carlo methods
Prof. Dr. Björn Eskofier
2021-11-30
IdM-login / Studon
00:11:37
3
Particle filtering
Prof. Dr. Björn Eskofier
2021-11-30
IdM-login / Studon
00:09:55
4
Particle filtering: example and algorithmic view
Prof. Dr. Björn Eskofier
2021-11-30
IdM-login / Studon
00:06:15
5
Recap
Prof. Dr. Björn Eskofier
2021-11-30
IdM-login / Studon
00:03:32
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction and concepts review
Dario Zanca
2021-12-07
IdM-login / Studon
00:10:29
2
Linear processes representation: AR and MA models
Dario Zanca
2021-12-07
IdM-login / Studon
00:21:49
3
ARMA and ARIMA
Dario Zanca
2021-12-07
IdM-login / Studon
00:13:48
4
Recap and critical analysis
Dario Zanca
2021-12-07
IdM-login / Studon
00:05:07
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Dario Zanca
2021-12-14
IdM-login / Studon
00:02:10
2
Data mining
Dario Zanca
2021-12-14
IdM-login / Studon
00:18:11
3
Frequency Analysis
Dario Zanca
2021-12-14
IdM-login / Studon
00:16:59
4
Dynamic time warping
Dario Zanca
2021-12-14
IdM-login / Studon
00:08:10
5
Other feature extraction methods for time series
Dario Zanca
2021-12-14
IdM-login / Studon
00:12:43
6
Recap and Python resources
Dario Zanca
2021-12-14
IdM-login / Studon
00:07:15
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Dario Zanca
2021-12-21
IdM-login / Studon
00:03:41
2
Deep learning basics
Dario Zanca
2021-12-21
IdM-login / Studon
00:18:57
3
Recurrent neural networks
Dario Zanca
2021-12-21
IdM-login / Studon
00:14:30
4
Backpropagation through time.
Dario Zanca
2021-12-21
IdM-login / Studon
00:06:54
5
Recap
Dario Zanca
2021-12-21
IdM-login / Studon
00:03:51
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Dario Zanca
2022-01-11
IdM-login / Studon
00:01:54
2
Long-term dependencies
Dario Zanca
2022-01-11
IdM-login / Studon
00:16:54
3
LSTMs
Dario Zanca
2022-01-11
IdM-login / Studon
00:11:25
4
Other gated architectures
Dario Zanca
2022-01-11
IdM-login / Studon
00:06:14
5
Recap
Dario Zanca
2022-01-11
IdM-login / Studon
00:02:09
Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction
Dario Zanca
2022-01-18
IdM-login / Studon
00:01:59
2
Convolutional Neural Networks (CNNs)
Dario Zanca
2022-01-18
IdM-login / Studon
00:16:32
3
Convolutional-based architectures
Dario Zanca
2022-01-18
IdM-login / Studon
00:12:30
4
Recap and critical comparison
Dario Zanca
2022-01-18
IdM-login / Studon
00:06:08

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