Book Content
chapters • 18h32m total length
1. Revisiting Machine Learning Basics
2. Practical Approach in Real-World Supervised Learning
3. Advanced Topics in Clustering and Anomaly Detection
4. Methodology for Real-world Semi-Supervised Learning
5. Real-time Stream Machine Learning
6. Probabilistic Graph Modelling
7. Deep Learning
8. Probabilistic Graph Modeling and Graph Data Learning
9. Related Topics in Machine Learning
10. Linear Algebra
11. Probability
