Study 24
- Search Algorithm
- Saddle point of optimizer
- RNN
- Bayesian Networks and Hidden Markov Models
- Clustering
- Sliding Mode
- Backstepping
- Denavit-Hartenberg (DH) Parameter
- Dimensionality Reduction & Matrix Factorization I
- Koordinate System, Euler Angle, Cardan Angle, Rotation Matrix
- Logical Agents
- Constraint Satisfaction Problems
- Flatness
- Feedback Linearization
- Passivity
- Support Vector Machines (SVM) and Kernels
- Deep Learning II
- Deep Learning I
- Optimization
- Linear Classification
- Linear Regression
- Probabilistic Inference : MLE, MAP, and Bayesian Estimation
- k-Nearest Neighbors Algorithm and Decision Tree
- Linearization & Phase Portraits