Iris Flower Classification

Email Spam Classification Model

Iris Flower Classfication is a popular machine learning project for the beginners. The dataset for this project was taken from kaggle.

Features:
  • Interactive Interface: Designed a user-friendly Streamlit application for real-time email classification.
  • Detailed Feedback:Provides clear and actionable results, indicating which type of iris flower has the given features.
  • High Accuracy: Achieved an accuracy of 97.5

Technologies Used:

  • Python
  • Streamlit:For building the interactive web application.
  • Pandas: For data manipulation and preprocessing.
  • Scikit-learn: For machine learning model training and evaluation.
  • Matplotlib and Seaborn:For data visualization.

Machine Learning Models
This project utilizes several machine learning models and techniques for classifying the Iris Flower:

  • Logistic Regression:Applied to classify the three types of Iris Flower: Setosa, Versicolor, Virginica based on their features. Achieved an accuracy of 97.5%

    • Project information