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 ===

  1. Search: Uninformed Search & Dynamic Programming
  2. Search: Informed Search
  3. Search: Genetic Algorithm
  4. MDP: Markov Decision Processes^
  5. MDP: Value Iteration^
  6. MDP: Reinforcement Learning^
  7. Games: Minimax, Expectimax, Evaluation Functions, Alpha-Beta Pruning^
  8. Games: TD Learning, Game Theory^
  9. Bayes: Bayesian Networks^
  10. Bayes: Hidden Markov Models^
  11. Bayes: Learning Bayesian Networks^
  12. Natural Language Processing
  13. Computer Vision
  14. Kuliah Tamu: Ethical AI

=== UAS ===

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

^^ Link mungkin tidak berfungsi di masa yang akan datang