Course Introduction

 

• Course Name: Machine Learning (Pembelajaran Mesin)
• Course Code: CSH3L3
• Credits : 3
  • 14 weeks of each:
    • 3 x 50’ class
    • 3 x 50’ structured tasks
    • 3 x 50’ self study

 

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Point Distribution

A	80 … 100.0
AB	75 … 79.99
B	70 … 74.99
BC	60 … 69.99
C	50 … 59.99
D	40 … 49.99
E	0 … 39.99

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Lecture Slides [2020]

1. Introduction to Machine Learning
2. Problem and Data Understanding
3. Evaluation Metrics
4. K-Means Clustering
5. Hierarchical Clustering
6. Naive Bayes
7. Support Vector Machine
   • [optional] SVM Detailed
8. Introduction to Artificial Neural Network
9. Gradient and Backpropagation
10. Bagging and Boosting
11. Reinforcement Learning

Lecture Slides [2019]

1. Introduction to Machine Learning
2. Introduction to Classification
3. Regression
4. Naïve Bayes
5. Artificial Neural Network
6. Probabilistic Neural Network
7. Support Vector Machine
8. Multi-Class SVM and Kernel Tricks
9. Clustering  (kMeans and Agglomerative)
10. Self-Organizing Maps
11. Reinforcement Learning Introduction
12. Reinforcement Learning part 2
13. Ensemble Methods – Bagging and Boosting
14. Ensemble Methods – Random Forest

 

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MISC

 

• Demo SVM Matlab
• Demo SVM Python

 

GitHub Exercise

 

• –

 

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Teaching History

 

• [2017/2018] – IF3909
• [2017/2018] – IF3910

 

• [2018/2019] – IFX4001
• [2018/2019] – IFX4202