Table of Contents
- Revisiting Machine Learning Basics
- Practical Approach in Real-World Supervised Learning
- Advanced Topics in Clustering and Anomaly Detection
- Methodology for Real-world Semi-Supervised Learning
- Real-time Stream Machine Learning
- Probabilistic Graph Modelling
- Deep Learning
- Probabilistic Graph Modeling and Graph Data Learning
- Related Topics in Machine Learning
- Linear Algebra
- Probability

