Artificial Intelligence & Machine Learning Semester Ganjil 2020/2021

Daftar Topik

1. Pengenalan Inteligensi Buatan & Agen Rasional
2. Classification: Decision Tree
3. Classification: k-NN
4. Praktik Klasifikasi
5. Classification: Neural Networks
6. Regression: Linear
7. Evaluation Metrics
8. Regression: Non-linear
9. Clustering: k-Means
10. Praktik Regresi & Clustering
11. Ensemble Learning
12. Searching: Uninformed Search
13. Searching: Informed Search
14. Local Search & Optimization: Hill Climbing

=== UTS ===

15. Search: Uninformed Search & Dynamic Programming
16. Search: Informed Search
17. Search: Genetic Algorithm
18. MDP: Markov Decision Processes^
19. MDP: Value Iteration^
20. MDP: Reinforcement Learning^
21. Games: Minimax, Expectimax, Evaluation Functions, Alpha-Beta Pruning^
22. Games: TD Learning, Game Theory^
23. Bayes: Bayesian Networks^
24. Bayes: Hidden Markov Models^
25. Bayes: Learning Bayesian Networks^
26. Natural Language Processing
27. Computer Vision
28. Kuliah Tamu: Ethical AI

=== UAS ===

^ Materi-materi ini diambil dari Stanford CS221: Artificial Intelligence^^

^^ Link mungkin tidak berfungsi di masa yang akan datang