Matrikulasi-Data Mining (A)
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Pengantar Data Mining
Pengantar Data Mining
Introduction to Data Mining
Praproses Data
Data Preprocessing
Data Preprocessing
Data Preprocessing
Feature Selection
Contoh Code Reduksi Dimensi
Section 3
Data Preprocessing
Handling Imbalanced Dataset
Imbalanced classes
Contoh Code handling imbalanced dataset
Section 4
Classification Methods
Basic Classification Concept
Tugas 1 Review Paper
Overfitting
Contoh code Decision Tree
Section 5
TM 05 : Lanjutan Metode Klasifikasi
kNN, ANN, Naive Bayes
paper drop-out ANN
Section 6
Diskusi Rule Based Classification & Association Rule
Tugas Klasifikasi
Tugas Rule Asosiasi
Section 7
Diskusi Association Rule (Lanjutan)
Section 8
TM08 : Diskusi Clustering
Section 9
Diskusi Metode Clustering DBScan
Metode Clustering
Section 10
Presentase Review Paper
Section 11
Presentase Review Paper
Pengantar Deep Learning
Section 12
Pengantar Deep Learning
Deep Sequence Model
Deep Computer Vision
Pertemuan ke-13
Diskusi Regresi
Dataset Studi Kasus
Dokumentasi Dataset
Dokumentasi DataSet 2
Regression Analysis
logistic regression
buku multivariat
Section 14
Logistic Regression
Section 15
Presentasi Regresi Multiple dan Regresi logistik
File Presentasi Regresi
Section 16
Unggah Revisi Presentasi Regresi
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Matrikulasi-Data Mining (A)
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Institut Teknologi Sepuluh Nopember
Doktor
Fakultas Teknologi Elektro dan Informatika Cerdas
S-3 ILMU KOMPUTER
Semester Gasal 2021/2022
Matrikulasi-Data Mining (A)
Summary
Matrikulasi-Data Mining (A)
Teacher:
Ahmad Saikhu
Teacher:
Chastine Fatichah