Python + Jupyter Projects
Machine Learning in Python
• Practiced supervised learning(K-Nearest Neighbor) on FIFA 2022 data
• Constructed confusion matrix to visualize prediction results
• Conducted unsupervised learning(K-Means Cluster) on FIFA 2022 data
• Used kneed package to find the elbow value based on inertia for different number of clusters to find the best k value
• Used silhouette_score to calculate silhouette scores for different number of clusters to find the best k value
Data Analysis and Visualization in Python
• Used Ordinary Least Square regression for data analysis of FIFA 2022
• Generated OLS regression results with statsmodels.formula.api package
• Interpreted statistics such as R-squared, correlation coefficient and p-value to make conclusions of data
• Made predictions using multiple linear regression
• Drew scatterplot using matplotlib.pyplot package