Machine learning is almost everywhere nowadays. It’s become more and more necessary day by day. From the recommendation of what to buy to recognizing a person, robotics, everywhere is machine learning. So in this project, we’ll create the “Hello World” of machine learning which means Iris flower classification.
Iris flower classification is a very popular machine learning project. The iris dataset contains three classes of flowers, Versicolor, Setosa, Virginica, and each class contains 4 features, ‘Sepal length’, ‘Sepal width’, ‘Petal length’, ‘Petal width’. The aim of the iris flower classification is to predict flowers based on their specific features. Dataset https://www.kaggle.com/datasets/uciml/iris
Steps to Classify Iris Flower:
- Load the data
- Analyze and visualize the dataset
- Model training.
- Model Evaluation.
- Testing the model.