/Intro-to-Machine-Learning

【 NYCU 2022 Fall Semester 】by Professor 林彥宇

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Introduction to Machine Learning

【 NYCU 2022 Fall Semester 】by Professor 林彥宇

Contents

HW1 $~$ Linear Regression using Gradient Descent

Implement linear regression by using only NumPy, then train implemented model using Gradient Descent by the provided dataset and test the performance with testing data.

HW2 $~$ Linear Discriminant Analysis

Implement Fisher’s linear discriminant by using only numpy, then train the model by the provided dataset and test the performance with testing data

HW3 $~$ Decision Tree, AdaBoost and Random Forest

Implement the Decision Tree, AdaBoost and Random Forest algorithm by using only NumPy, then train implemented model by the provided dataset and test the performance with testing data.

HW4 $~$ Support Vector Machine

Implement the Cross-validation and grid search by using only NumPy, then train the SVM model from scikit-learn by the provided dataset and test the performance with testing data.