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Course Description
The Machine Learning course trains students to understand basic ideas, intuition, concepts, algorithms and techniques to make computers smarter through the process of learning from data. The material presented includes supervised learning, unsupervised learning, reinforcement learning, and ensemble methods.
Program Objectives (PO)
- Mahasiswa mampu menjelaskan konsep dari setiap metode machine learning
- Mahasiswa mampu mengidentifikasi, memodelkan, menganalisis, dan menyelesaikan permasalahan menggunakan metode-metode machine learning.
- Mahasiswa mampu mengimplementasikan metode-metode machine learning menggunakan bahasa pemrograman untuk menyelesaikan permasalahan
Aktifitas Pembelajaran
-
Pertemuan 1 Konsep dan motivasi machine learning. -
Pertemuan 2 Mengidentifikasi, memodelkan, menganalisis, dan menyelesaikan masalah menggunakan regresi -
Pertemuan 3 Konsep Naïve Bayes -
Pertemuan 4 Konsep, mengidentifikasi, memodelkan, menganalisis, dan mengimplementasikan Probabilistic Neural Network untuk menyelesaikan masalah klasifikasi -
Pertemuan 5 Konsep, mengidentifikasi, memodelkan, menganalisis, dan mengimplementasikan Probabilistic Neural Network untuk menyelesaikan masalah klasifikasi -
Pertemuan 6 Konsep Support Vector Machine -
Pertemuan 7 Konsep Support Vector Machine -
Pertemuan 8 Konsep hierarchical clustering -
Pertemuan 9 Konsep hierarchical clustering -
Pertemuan 10 Konsep Self-Organizing Maps -
Pertemuan 11 Konsep Reinforcement learning -
Pertemuan 12 Konsep Reinforcement learning -
Pertemuan 13 Konsep Ensemble methods -
Pertemuan 14 Konsep Ensemble methods -
Pertemuan 15 Konsep Ensemble methods -
Pertemuan 16 Ujian Akhir Semester
References
Lecturer
Difficult Things About Education.
$75$10
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