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Topics to be covered
Topics to be covered
- Data exploration and visualization
- Supervised learning (or predictive analysis): Regression, Classification
- Unsupervised learning (or descriptive analysis): Clustering, Dimension reduction
- Evaluation and model assessment
- Special topics: Network mining, Text mining, Recommendation
- Selected topics (TBD): advanced clustering and classification techniques, outliner analysis, big data science research trends, etc.
Tentative schedule
Tentative schedule
*Note: Students are required to attend the Big Data Science Colloquium (details to be provided), and the class will be occasionally re-scheduled if conflicting with the colloquium schedule.
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