Recurrent Neural Networks (RNNs)
Data Science · University of Applied Sciences · Artificial Intelligence
This unit introduces Recurrent Neural Networks (RNNs), a type of deep learning model designed to handle sequential data. Students will learn the architecture, types (e.g., LSTM, GRU), and applications of RNNs in natural language processing and time series analysis.
Zum Üben gibt es 56 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- RNN Architecture
- Types of RNNs (LSTM
- GRU)
- Applications of RNNs in Natural Language Processing
- Applications of RNNs in Time Series Analysis
- Challenges in Training RNNs
- Backpropagation Through Time
- Vanishing Gradient Problem
Stichworte
- LSTM
- GRU
- Natural Language Processing
- Time Series Analysis
- Applications of RNNs