Machine Learning Projects

This repository contains Python projects demonstrating the three main types of machine learning models: Regression, Classification, and Clustering.

Language(s): Python
Package(s): Scikit-learn, Pandas, Seaborn, Statsmodels, Joblib
Software: Jupyter Notebooks

Current Projects:

• Predicting Insurance Costs with Multiple Linear Regression: Creates, evaluates, and deploys a Multiple Linear Regression model capable of predicting insurance costs based on patient information (age, sex, bmi, smoking status, number of children, and region of residence).

Projects Coming Soon:

• Poison Mushroom Classification: Compares the performance of 7 Classification models (Logistic Regression, KNN, SVM, Single Decision Tree, Random Forest, AdaBoost, and GradientBoost) in predicting whether a mushroom is poisonous given information on appearance, odor, habitat, and more.
• Polynomial Regression: Creating a non-linear regression model capable of accurately predicting a continuous outcome based on labeled historical data.
• Clustering: Compares 2 Machine Learning models (K-Means and DBSCAN) on their ability to group unlabeled data based on feature similarities.