CodSoft-DataScience-Internship
This project uses the Iris dataset to develop a machine learning model that classifies Iris flowers into three species: setosa, versicolor, and virginica. The workflow includes data exploration, preprocessing, visualization, and model training using a Support Vector Machine (SVM). The project also features a user interaction component for predicting species based on input measurements.
Key steps:
- Import and explore data.
- Preprocess and encode data.
- Visualize data relationships.
- Split data into training and testing sets.
- Train and evaluate an SVM model.
- Allow user predictions based on flower measurements.