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Course Outline
Pengantar Aplikasi Machine Learning
- Pembelajaran statistik vs. Pembelajaran mesin
- Iterasi dan evaluasi
- Tambahan bias-varians
Machine Learning dengan Python
- Pilihan perpustakaan
- Alat tambahan
Regresi
- Regresi linier
- Pengembangan dan Nonlinearitas
- Tugas praktikum
Klasifikasi
- Pembaruan Bayesian
- Naive Bayes
- Regresi logistik
- K-Tetangga terdekat
- Tugas praktikum
Cross-validation dan Resampling
- Metode cross-validation
- Bootstrap
- Tugas praktikum
Unsupervised Learning
- Klasterisasi K-means
- Contoh-contoh
- Tantangan pembelajaran tak terawasi dan di luar K-means
Requirements
Kemahiran dalam bahasa pemrograman Python. Kebiasaan mendasar dengan statistik dan aljabar linear disarankan.
14 Hours
Testimonials (5)
The trainer showed that he has a good understanding of the subject.
Marino - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days
It was a great intro to ML!! I liked the whole thing, really. The organization was perfect. The right amount of time for lectures/ demos and just us playing around. Lots of topics were touched, just at the right level. He was also very good at keeping us super engaged, even without any camera being on.
Zsolt - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days
Clarity of explanation and knowledgeable response to questions.
Harish - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days
The knowledge of the trainer was very high and the material was well prepared and organised.
Otilia - TCMT
Course - Machine Learning with Python – 2 Days
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
