Data Mining
Techniques for discovering patterns, associations, and knowledge from large datasets. Covers classification, clustering, association rule mining, and anomaly detection.
Instructor: Tushar R. Mahore
Term: AY 2024–25
Location: Pimpri Chinchwad University, Pune
Course Overview
Data mining bridges database systems and machine learning — extracting actionable knowledge from raw data. This course covers the core algorithmic toolkit and practical workflows.
Topics Covered
- KDD process and data preprocessing
- Classification: Decision Trees, Naïve Bayes, k-NN, SVM
- Clustering: k-Means, hierarchical, DBSCAN
- Association rule mining: Apriori, FP-Growth
- Anomaly / outlier detection
- Regression and prediction
- Text mining and web mining basics
- Evaluation metrics for mining tasks
Tools
Python (Scikit-learn, NLTK), Weka, KNIME
Materials
Course materials will be uploaded here. Contact mahoretushar@gmail.com for resources.