Machine Learning

Description

In this course, you will learn:

• To provide a broad overview of machine learning methodologies and techniques.
• To have a better understanding of various major machine learning topics.
• To improve your design and programming skills so that you can create intelligent, adaptive artefacts.
• Develop the fundamental abilities required to undertake machine learning research.

Syllabus:

1. ML is the ROX/SL 1- Decision Trees
2. Regression and Classification
3. Neutral Networks
4. Instance-Based Learning
5. Ensemble B&B
6. Kernel Methods & SVMs
7. Comp Learning Theory
8. VC Dimensions
9. Bayesian Learning
10. Bayesian Inference
11. Randomized Optimization
12. Clustering/ UL 3- Feature Selection
13. Feature Transformation/UL 5- Info Theory
14. Markov Decision Processes
15. Reinforcement Learning
16. RL 3 Game Theory/Outro