Unsupervised Learning
Master of Science in Computer Science · University · Artificial Intelligence
This unit introduces unsupervised learning, a fundamental technique in AI for analyzing unlabeled data. Students will learn about clustering, dimensionality reduction, and anomaly detection, enabling them to extract meaningful insights and patterns from complex datasets.
Zum Üben gibt es 52 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)
- Anomaly Detection Algorithms (e.g.
- isolation forest
- local outlier factor)
- Applications of Unsupervised Learning in Different Domains
Stichworte
- Clustering
- Dimensionality Reduction
- Anomaly Detection
- Unsupervised Learning
- Machine Learning
- Data Analysis
- Pattern Recognition