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Machine Learning for Business Decision Making
OVERVIEW
CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: 17661
Transcript Source: Partner Institution
Course Details: Level 400
Recommended Semester Credits: 3
Contact Hours: 42
DESCRIPTION
1. Introduction to Machine Learning
2. Data Extraction and Exploration
3. Basic models for classification and regression
3.1. Nearest neighbor
3.2. Trees and rules
4. Feature Generation and Selection
5. Methodology: training, hyper-parameter tuning, model evaluation
6. Advanced models for classification and regression
6.1. Bagging, Random Forest
6.2. Boosting
6.3. Stacking
6.4. Support Vector Machines
7. Data clustering
8. Associative Learning
2. Data Extraction and Exploration
3. Basic models for classification and regression
3.1. Nearest neighbor
3.2. Trees and rules
4. Feature Generation and Selection
5. Methodology: training, hyper-parameter tuning, model evaluation
6. Advanced models for classification and regression
6.1. Bagging, Random Forest
6.2. Boosting
6.3. Stacking
6.4. Support Vector Machines
7. Data clustering
8. Associative Learning
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