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Lecture 1
Introduction & pattern classification concept
Pendahuluan, prinsip pengenalan pola dengan pemilihan fitur
Assigment 1: Penggunaan Weka untuk klasifikasi dengan UCI dataset
Lecture 3
Clustering
Clustering
Lecture 4
Presentasi Tugas 1 & Decision Tree
Decision Tree
Lecture 5
Classifier & SVM
Classifier & SVM
Assignment 2: paper analysis
Lecture 6
Neural Networks
Neural Networks
Lecture 7
Paper analysis, RBFN & Kohonen network
RBFN & Kohonen network
Lecture 8
FIS & ANFIS
FIS & ANFIS
Lecture 9
Midterm (paper analysis)
Pengumpulan jawaban midterm
Midterm (paper analysis)
Lecture 10
PCA, LDA, ICA
PCA, LDA, ICA
Assignment 3: paper implementation
Lecture 11
GA, ACO, PSO
GA, ACO, PSO
Lecture 12
FFT, Wavelet, assignment 3 presentation
FFT, Wavelet
Lecture 13
Intro to CNN
Intro to CNN
Project proposal
Lecture 14
Project proposal presentation
Lecture 15
Final project assignment
Project progress
Lecture 16
Final project presentation/demo
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Side panel
Panduan Dosen
Unduh PDF
[Video] Panduan Membuat Video Asinkronus dengan Power Point
Panduan Mahasiswa
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Kecerdasan Komputasional (B)
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Institut Teknologi Sepuluh Nopember
Magister
Fakultas Teknologi Elektro dan Informatika Cerdas
S-2 TEKNIK INFORMATIKA
Semester Gasal 2021/2022
Kecerdasan Komputasional (B)
Summary
Kecerdasan Komputasional (B)
Teacher:
Handayani Tjandrasa