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University of Gothenburg
Neural Networks
<p>The course gives an overview and a fundamental theoretical understanding of the most important neural net algorithms. These include models of associative memory algorithms for learning from examples (e.g., perceptron learning, back-propagation, temporal difference learning), and models for self-organization. Thro…
- Higher education
- Information unavailable
- 2 September 2024
- Information unavailable
- Information unavailable
- 50 %
Overview
<p>The course gives an overview and a fundamental theoretical understanding of the most important neural net algorithms. These include models of associative memory algorithms for learning from examples (e.g., perceptron learning, back-propagation, temporal difference learning), and models for self-organization. Through comparison with methods from statistics and computer science students can develop an understanding of when neural networks are useful in application problems.</p>
Admission scores
Entry requirements
A Bachelor's degree in Engineering, Natural or Mathematical sciences of 180 credits including knowledge of Mathematical analysis, Linear algebra and Programming. Applicants must prove their knowledge of English: English 6/English B from Swedish Upper Secondary School or the equivalent level of an internationally recognized test, for example TOEFL, IELTS.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2024-09-02
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.fim720.11160.20242
- Last checked
- 2026-09-23T10:36:47.551594+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
Programme content
Study structure
Application and important dates
- Programme or course starts
- Programme or course ends
Salary and salary distribution
Common occupations after graduation
Students
Geographical background
Previous upper-secondary schools and programmes
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.gu.fim720.11160.20242
- Offering identity in the source
- e.uoh.gu.fim720.11160.20242
- Education-form source code
- HS
- Education code in the source
- FIM720
- Change time according to the source
- 2024-03-04T11:53:11
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.