Course Description :
Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.
Other Resources :
Other Computer Science Courses
- Multicore Programming Primer by MIT
- Programming Languages and Compilers by UC Berkeley
- Computer System Engineering by MIT
- Data Structures And Algorithms by IIT Delhi
- Visual Basic by Other
- Parallel Computation by University of Washington
- Computer Networks by IIT Kharagpur
- Systems Analysis and Design by IISc Bangalore
- CSEP 524 Parallel Computation by University of Washington
- Introduction to Computer Science I by Harvard
» check out the complete list of Computer Science lectures
Get Your Degree!
Find schools and get information on the program that’s right for you.
Powered by Campus Explorer