Transformers
Master of Science in Computer Science · University · Machine Learning
This unit introduces the architecture and attention mechanisms of Transformer models, exploring their applications in natural language processing. Students will gain hands-on experience with Transformers for tasks such as text classification, machine translation, and question answering.
Zum Üben gibt es 50 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Transformer Architecture
- Encoder and Decoder Stacks
- Attention Mechanisms
- Self-Attention
- Multi-Head Attention
- Positional Encoding
- Applications in Natural Language Processing
- Text Classification
- Machine Translation
- Question Answering
- Advantages and Disadvantages of Transformers
- Current and Future Research Directions
Stichworte
- Natural Language Processing
- Deep Learning
- NLP Applications