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Machine learning Overview PD. Dr. Gabriella Kókai [email_address] Friedrich-Alexander-Universität Lehrstuhl für Informatik 2 Raum 04.131 Tel: 8528996
Machine Learning: Content ,[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning? (1/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning? (2/10) ,[object Object],[object Object],Machine Learning Cognitive Science Statistic Pattern Recognition Computer Science
Why Machine Learning? (3/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning?(4/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning?(5/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning? (6/10) ,[object Object],[object Object],[object Object]
Why Machine Learning? (7/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning? (8/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning? (9/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Why Machine Learning? (10/10) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
How can the learning problem be defined ,[object Object],[object Object],[object Object],[object Object],[object Object]
Content ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choosing the Training Experience (1/2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choosing the Training Experience (2/2) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Choosing the Target Function (1/2) ,[object Object],[object Object],[object Object],[object Object]
Choosing the Target Function (2/2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choosing a Function Approximation Algorithm (1/2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choosing a Function Approximation Algorithm (2/2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Choosing a Function Approximation Algorithm: Estimating Training Values ,[object Object],[object Object],[object Object]
Choosing a Function Approximation Algorithm: Adjusting the Weights ,[object Object],[object Object],[object Object],[object Object],[object Object]
Some Issues in Machine Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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vorl1.ppt

  • 1. Machine learning Overview PD. Dr. Gabriella Kókai [email_address] Friedrich-Alexander-Universität Lehrstuhl für Informatik 2 Raum 04.131 Tel: 8528996
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