| Kode Mata Kuliah | MA6083 / 4 SKS |
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| Penyelenggara | 201 - Matematika / FMIPA |
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| Kategori | Kuliah |
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| Bahasa Indonesia | English |
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| Nama Mata Kuliah | Teori Pembelajaran Statistik | Statistical Learning Theory |
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| Bahan Kajian | - Dasar-dasar teori prediksi statistik
- Ketaksamaan konsentrasi (Concentration inequalities)
- Supervised and unsupervised learning
- Minimisasi risiko empris
- Optimisasi untuk pembelajaran mesin (machine
learning)
- Perkembangan teori baru dan aplikasi dalam pembelajaran mendalam (deep learning)
| - Fundamentals of statistical prediction theory.
- Concentration inequalities.
- Supervised and unsupervised learning.
- Empirical Risk Minimization
- Optimization for machine learning.
- Recent theoretical developments and applications in deep learning.
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| Capaian Pembelajaran Mata Kuliah (CPMK) | - Memahami analisis teoritikal dari pembelajaran mesin secara statistic dan pembelajaran mendalam.
- Memahami aplikasi teori pembelajaran statistik dalam mendesain algoritma pembelajaran mesin
- Mampu menggunakan teori pembelajaran statistic untuk menyelesaikan masalah real atau studi kasus atau tantangan baru
| - Understand the statistical theoretical analysis of machine learning and deep learning.
- Understand the application of statistical learning theory in the design of machine learning algorithms.
- Be able to apply statistical learning theory to solve real-world problems, case studies, or emerging challenges.
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| Metode Pembelajaran | Ceramah, diskusi, pembelajaran berbasis masalah | Lecture, Discussion, Problem Based Learning |
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| Modalitas Pembelajaran | Sinkron/asinkron, Mandiri/kelompok | Synchronous/asynchronous, Independent/group |
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| Jenis Nilai | ABCDE |
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| Metode Penilaian | ujian, tugas, praktikum | exams, assignments, practicum |
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| Catatan Tambahan | | |
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