Lec9 Decision Trees

Lec10 Linear Discrimination

Lec11 Multilayer Perceptron

Lec12 Deep Learning

Lec13 Local Models

Lec14 Kernel Machines

기말고사

1. Decisions Tree with pseudo code
   1. Early Stop
   2. If x is numeric, what does mean ‘for all possible split’
2. 2번 Likelihood vs Discriminated Representation
3. Reason why we set weights to small values (Gradient Vanishing)
4. MLP
   1. What is embedding
   2. Transfer Learning
5. Overtraining
6. How to update weights of RNN
7. Kernel Functions
   1. What is Kernel Trick using the equation
   2. What are alpha and r
   3. Example