Building Transformer-Based Natural Language Processing Applications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10256185" target="_blank" >RIV/61989100:27740/24:10256185 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/22:10249843
Result on the web
<a href="https://events.it4i.cz/event/216/" target="_blank" >https://events.it4i.cz/event/216/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Building Transformer-Based Natural Language Processing Applications
Original language description
In this course participants learned how to use Transformer-based natural language processing models for text classification tasks, such as categorizing documents. They also learned how to leverage Transformer-based models for named-entity recognition (NER) tasks and how to analyze various model features, constraints, and characteristics to determine which model is best suited for a particular use case based on metrics, domain specificity, and available resources.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů