Introduction To Machine Learning For Economists – Bologna

Argomenti del programma: 1. Introduction to Statistical Learning 2. Regression, Classification, Resampling Methods 3. Supervised Learning I: Linear Models Linear Model Selection and Regularization (LASSO and Ridge regression) Bias/Variance Trade-off, Overfitting, Validation 4. Supervised Learning II: Nonlinear Models Tree-based methods (Trees, Random Forests, Bagging, Boosting) Support Vector Machines and Neural Networks 5.

Argomenti del programma: 1. Introduction to Statistical Learning 2. Regression, Classification, Resampling Methods 3. Supervised Learning I: Linear Models Linear Model Selection and Regularization (LASSO and Ridge regression) Bias/Variance Trade-off, Overfitting, Validation 4. Supervised Learning II: Nonlinear Models Tree-based methods (Trees, Random Forests, Bagging, Boosting) Support Vector Machines and Neural Networks 5.