- π Iβm currently in a data science internship working on matching retail data.
- π± Iβm currently learning about sampling techniques and statistical data science.
- π― Iβm looking to collaborate on Data Science projects and internships.
- π€ Iβm interested in Data Analytics and Business Analytics.
- π« How to reach me: [email protected] or https://www.linkedin.com/in/shantongkwok/
jasminekwok / election2016-analysis Goto Github PK
View Code? Open in Web Editor NEWThis project aims to recreate some of the machine learning methods Nate Silver used in 2016, by using the actual election data and determining how accurate some of these methods were at predicting the final results. The methods we used were Principal Component Analysis, Hierarchical Clustering, Decision Trees, Logistic Regression and Lasso Regularization. In addition to using those methods, we performed other classification methods such as K-Nearest Neighbors and Random Forest and explored the possibility of Simpsonβs Paradox in our dataset used for the algorithms.