Course Description :
introduction,The Motivation Applications of Machine Learning - An Application of Supervised Learning - Autonomous Deriving - The Concept of Under fitting and Over fitting - Newtons Method - Discriminative Algorithms - Multinomial Event Model - Optimal Margin Classifier - Kernels - Bias/variance Trade off - Uniform Convergence - The Case of Infinite H - Bayesian Statistics and Regularization - The Concept of Unsupervised Learning - Mixture of Gaussian-The Factor Analysis Model - Latent Semantic Indexing (LSI) - Applications of Reinforcement Learning - Generalization to Continuous States - State-action Rewards - Advice for Applying Machine Learning - Partially Observable MDPs (POMDPs).
Get Your Degree!
Find schools and get information on the program that’s right for you.
Powered by Campus Explorer
Other Resources :
Other Computer Science Courses
- Logic for Computer Science by IIT Delhi
- Design and Analysis of Algorithms by IIT Bombay
- Structure and Interpretation of Computer Programs by MIT
- XML with,Java Servlet,and JSP by Harvard
- Computer Science III: Programming Paradigms by Stanford
- Systems Analysis and Design by IISc Bangalore
- CSE 30341 Operating Systems by Other
- Innovative Computing by Harvard
- Software Engineering III by Other
- Introduction to Computer Science and Programming by MIT
» check out the complete list of Computer Science lectures