Drug Classification Using Machine Learning

Description:

This project focuses on building a predictive model to classify drugs based on various medical features. It involves real-world health data, with preprocessing steps like handling unnecessary columns, data visualization, and cleaning. The cleaned data is then used to train and evaluate machine learning models for accurate classification.

Main Steps:

Data loading and cleaning using Pandas

Exploratory Data Analysis (EDA) using NumPy, Matplotlib, and Seaborn

Data preprocessing (dropping irrelevant columns)

Model training using Scikit-learn

Evaluation using performance metrics (accuracy, confusion matrix, etc.)

Tools & Libraries Used:

Python

Pandas

NumPy

Matplotlib

Seaborn

Scikit-learn