Statistical Machine Learning (K)
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Semester Learning Plan (Rencana Pembelajaran Semester - RPS)
RPS
WEEK 1
Introduction to SML
WEEK 2
Sesi 1 Bagus Sartono - Teknik Pembelajaran Mesin
Unsupervised method - Clustering Methods
A Comprehensive Survey of Clustering Algorithms
Unsupervised method - Clustering Methods
A Comprehensive Survey of Clustering Algorithms
Unsupervised method - Clustering Methods
A Comprehensive Survey of Clustering Algorithms
WEEK 3 & 4
Supervised Learning - Logistic Regression
Supervised learning - SVM
WEEK 5
Support Vector Regression (SVR) for prediction
Time Series Clustering
Time-Series Clustering in R Using the dtwclust Package (the R Journal)
TSclust - An R package for time series forecasting (Journal of Stat Soft)
WEEK 6
Decision Trees in R
Decision Tree and Random Forest
WEEK 7 & 8
Feature Selection dan Performance Evaluation
Corporate Financial Distress Prediction using Statistical Extreme Value-based Modeling and Machine Learning
Handing Imbalanced Dataset - GEVR approach
WEEK 9 & 11
Introduction to Neural Network
Single layer perceptron
single layer NN for regression
case study (single layer perceptron)
Week 12
buku Fundamental of NN
NN MLP
Backpropagation
Neural Network for Time Series Forecasting
Neural Network for Time Series Forecasting
The Performance of Ramsey Test, White Test and Terasvirta Test in Detecting Nonlinearity
Design of Experiment to Optimize the Architecture of Deep Learning for Nonlinear Time Series Forecasting
Week 13-14
CC GENERAL.csv
PROJETC 1 (individual)
Individual project
PROJECT 2 (group)
Do in group
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Statistical Machine Learning (K)
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Institut Teknologi Sepuluh Nopember
Sarjana
Fakultas Sains dan Analitika Data
S-1 STATISTIKA KELAS INTERNASIONAL
Semester Gasal 2023/2024
Statistical Machine Learning (K)
Summary
Statistical Machine Learning (K)
Teacher:
Dedy Dwi Prastyo