Machine Learning for Engineers I 2022/2023 /KursID:3261
- Letzter Beitrag vom 2022-12-01

Einrichtung

Lehrstuhl für Maschinelles Lernen und Datenanalytik

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Vorlesungsreihe

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Studon

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Kurskapitel

Folge
Titel
Lehrende(r)
Aktualisiert
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Dauer
Medien
1
Organizational Information
Prof. Dr. Björn Eskofier
2022-10-18
Studon
00:05:58
2
Motivation 1
Prof. Dr. Björn Eskofier
2022-10-18
Studon
00:08:12
3
Motivation 2
Prof. Dr. Björn Eskofier
2022-10-18
Studon
00:12:19
4
Machine Learning Types Supervised Learning
Prof. Dr. Björn Eskofier
2022-10-18
Studon
00:14:35
5
Machine Learning Types Unsupervised Learning
Prof. Dr. Björn Eskofier
2022-10-18
Studon
00:10:33
6
Machine Learning Types Reinforcement Learning
Prof. Dr. Björn Eskofier
2022-10-30
Studon
00:04:13
7
Machine Learning Pipeline
Prof. Dr. Björn Eskofier
2022-10-19
Studon
00:14:15
8
Summary
Prof. Dr. Björn Eskofier
2022-10-19
Studon
00:02:32
Folge
Titel
Lehrende(r)
Aktualisiert
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Dauer
Medien
1
Linear Regression Motivation
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:03:05
2
Linear Regression Motivation Example
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:07:36
3
Linear Regression Overall Picture
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:04:49
4
Linear Regression The Linear Model
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:13:21
5
Linear Regression Optimization (1/3)
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:06:43
6
Linear Regression Optimization (2/3)
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:11:35
7
Linear Regression Optimization (3/3)
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:08:52
8
Basis Functions
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:11:04
9
Logistic Regression Motivation
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:06:18
10
Logistic Regression The Logistic Model
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:07:12
11
Logistic Regression Optimization
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:08:01
12
Overfitting & Underfitting
Prof. Dr. Björn Eskofier
2022-10-14
Studon
00:12:12
Folge
Titel
Lehrende(r)
Aktualisiert
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Dauer
Medien
1
Problem Statement (1/2)
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:06:12
2
Problem Statement (2/2)
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:05:47
3
Optimization Intro
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:05:23
4
Optimization: Solution using Partial Derivatives
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:05:57
5
Optimization Summary
Prof. Dr. Björn Eskofier
2022-12-01
Studon
00:01:55
6
SVM Basis Functions
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:04:48
7
Intro to Kernel Trick
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:08:04
8
SVM Types of Kernels
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:05:47
9
SVM Hard and Soft Margin
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:06:51
10
SVM Regression
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:07:39
11
SVM Summary
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:03:48
Folge
Titel
Lehrende(r)
Aktualisiert
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Dauer
Medien
1
Intuition
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:07:20
2
Mathematics 1
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:05:33
3
Mathematics 2
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:07:08
4
Applications
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:10:56
5
Summary
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:03:03
Folge
Titel
Lehrende(r)
Aktualisiert
Zugang
Dauer
Medien
1
Perceptron
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:09:32
2
Multilayer Perceptron
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:07:46
3
Loss function
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:10:43
4
Gradient Descent
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:10:10
5
Learning Process
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:07:11
6
Convolution
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:10:35
7
Pooling
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:08:09
8
Applications
Prof. Dr. Björn Eskofier
2022-10-16
Studon
00:06:10

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