Unsupervised Learning for NLP
Machine Learning · Further Education · Natural Language Processing
This unit introduces unsupervised learning, a fundamental technique in NLP. Students will explore methods like clustering, dimensionality reduction, and topic modeling, gaining practical skills in applying these techniques to real-world NLP tasks.
Zum Üben gibt es 56 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to Unsupervised Learning
- Clustering Algorithms (e.g.
- k-means
- hierarchical clustering)
- Dimensionality Reduction Techniques (e.g.
- PCA
- LDA)
- Topic Modeling (e.g.
- LDA
- NMF)
- Applications of Unsupervised Learning in NLP (e.g.
- text clustering
Stichworte
- Clustering
- Dimensionality Reduction
- Topic Modeling
- NLP Applications
- Unsupervised Learning Algorithms
- Evaluation Metrics