- In Jupyter Notebook, utilizing many libraries for Python such as pandas, numpy, matplotlib, seaborn, etc.
- With a team of 3 classmates, using data from UCI Machine Learning to complete a data science project from start to finish including: Problem, Data Preprocessing, Data Cleaning, Explotary Data Analysis, Modeling, Communication.
- Construct three models using three different supervised learning methods: KNN, Naives Bayes, and Random Forest to predict which patient has diabetes. Analyze, realize pros and cons, and give conclusions on the performance of each method when dealing with the dataset.