• Supervised Machine Learning (A)
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    SD234504 - Supervised Machine Learning
    Rencana Pembelajaran Semester
    Announcements
    Announcements
    Introduction to Machine Learning
    Book: Yu-Wei, David Chiu - Machine Learning with R Cookbook_ Explore over 110 recipes to analyze data and build predictive models with the simple and easy-to-use R code-Packt Publishing (2015)
    Article: Prescriptive analytics - Literature review and research challenges
    Article: 50 Years of Data Science
    Week #1 - Introduction to machine learning (continued)
    credit-earning program of BDC competition: session 1 (Bagus Sartono) - Teknik Pembelajaran Mesin
    credit-earning program of BDC competition: session 2 (Rangga Pratama) - Clustering in Business
    credit-earning program of BDC competition: session 3 (Dedy Dwi Prastyo) - Unsupervised Machine Learning
    credit-earning program of BDC competition: session 4 (Setia Pramana) - Bioscience Machine Learning
    credit-earning program of BDC competition: session 5 (Sri Astuti Thamrin) - Supervised Learning (part 1)
    credit-earning program of BDC competition: session 6 (Siti Mariyah) - Pemanfaatan Statistical Machine learning pada official statistics
    credit-earning program of BDC competition: session 7a (R Bagus Fajriya Hakim) - Supervised Learning (part 2)
    credit-earning program of BDC competition: session 7b (R Bagus Fajriya Hakim) - SVM
    credit-earning program of BDC competition: session 7c (R Bagus Fajriya Hakim) - ANN
    credit-earning program of BDC competition: session 8 (Yunanto Cahyo Putranto) - Business Intelligence
    Week 1 and 2
    Introduction to Machine Learning
    Slide-2: Data Analytics
    Week 2 - Classification using Discriminant Analysis
    slide of the MVA book (Haerdle and Simar) - Discriminant Analysis
    Gaussian Discriminant Analysis, including QDA and LDA
    Discriminant Analysis in R
    DiscriminantAnalysis.R
    Praktikum 4 September 2025 mulai pukul 13:00 WIB
    Week 3 - Classification using Logistic Regression
    Classification using Logistic Regression
    Week #4 - Decision Tree
    Tree-based Methods
    Decision Tree and Random Forest
    Week #4 & #5 - Random Forest
    Random Forest for Regresion
    slide-6: Supervised learning: Decision Tree and Random Forest (updated)
    Week #5 - #6 Support Vector Machine
    slide-3: Supervised Learning: Logistic Regression
    slide-4: Supervised learning: SVM for Classification
    illustration: SVM with polynomial kernel visualization
    Week #7 - Support Vector Regression
    Support Vector Regression - a tutorial (1)
    Support Vector Regression - a tutorial (2)
    slide-5: Support Vector Regression (simulation) updated Sept-2021
    Materials
    Lecture Notes
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    Supervised Machine Learning (A)
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    Supervised Machine Learning (A)

    • Teacher: Dedy Dwi Prastyo
    • Teacher: Novri Suhermi

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    Sukolilo | Manyar | Tjokroaminoto
    Kampus Institut Teknologi
    Sepuluh Nopember Surabaya
    Phone: 031-5994251-54, 5947274, 5945472
    Fax: 031-5923465, 5947845

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