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Katalog Kelas
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Tech Deep-dive
Problem Based
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Credit Scoring Modeling
General
General
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Topik 3.3: One-hot Encoding
Topik 3.5: Scaling, Split Training dan Testing Data Set
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Topik 3.4: Imbalance Data Set
Topik 3.4: Imbalance Data Set
Topik 3.4: Imbalance Data Set
3.4.1 Oversampling dan Undersampling
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3.4.2 Imbalance Data Coding
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Topik 3.3: One-hot Encoding
Topik 3.5: Scaling, Split Training dan Testing Data Set
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Deskripsi Kelas
Topik 1.1 : Selamat Datang di Kelas Credit Scoring
Topik 1.2 : Quick MBA for Bankers
Topik 1.3: Pinjaman Kartu Kredit
Topik 1.4: Manajemen Risiko Kredit
Topik 1.5: Penutupan Bagian I
Topik 2.1: Persiapan Python
Topik 2.2: Mencari Nilai Kosong (Missing Value)
Topik 2.3: Data Eksplorasi
Topik 2.4: Data Visualisasi #1
Topik 2.5: Data Visualisasi #2
Topik 2.6: Analisa Statistik #1
Topik 2.7: Analisa Statistik #2
Topik 2.8: Analisa Statistik #3
Topik 2.9: Penutupan Bagian II
Topik 3.1: Pembukaan dan Persiapan untuk Data Preparation
Topik 3.2: Feature Engineering
Topik 3.3: One-hot Encoding
Topik 3.5: Scaling, Split Training dan Testing Data Set
Topik 3.6: Penutupan Bagian III
Topik 4.1: Modeling
Topik 4.2: Model Logistic Regression
Topik 4.3: Model Decision Tree
Topik 4.4: Model Random Forest
Topik 4.5: Model xGB
Topik 4.6: Model Scorecard with Logistic Regression
Topik 4.7: Penutupan Bagian IV
Topik 5.1: Evaluasi dan Implementasi Model
Topik 5.2: Confusion Matrix
Topik 5.3: Classification
Topik 5.4: Gain and Lift Chart
Topik 5.5: Kolmogorov-Smimov
Topik 5.6: AUC-ROC dan Gini Cofficient
Topik 5.7: Summary dan Tugas Akhir
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