Intro to Machine Learning Class in NYCU, 2021.09~2022.01
In mushroom and Iris dataset, construct Naive Bayes classifier to classify.
run hw1_Iris.ipynb
run hw1_mushroom.ipynb
In Student Performance Data Set, build Decision Tree & Random Forest & KNN & PCA to classify.
run hw2.ipynb
In Wheat Seeds Dataset build K-means Clustering to classify.
In Ionosphere Dataset build Support Vector Machine to classify good or bad.
run hw3_seeds_dataset.ipynb
run hw3_inonsphere.ipynb
Build Linear Regression & Logistic Regression.
run hw4.ipynb
In Recipe Ingredients Dataset, build Artificial Neural Networks to predict the category of dish.
run hw5.ipynb
using one cuban's daily eating habits open dataset to preprocess and label, goal to classification food categority, and using Decision Tree,Random Forest,KNN to compare performance
run final_project.ipynb