Image classification using ML
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Description:
The Iris Flower Classification project classifies different species of the Iris flower based on features like sepal length, sepal width, petal length, and petal width. It is often used to demonstrate machine learning algorithms.
Features:
- Classify iris flower species (setosa, versicolor, virginica).
- Use machine learning models like Decision Trees, SVM, or KNN for classification.
Requirements:
- Programming Language: Python
- Libraries/Tools:
- Scikit-learn for classification.
- Pandas for data manipulation.
- Matplotlib for visualization.
Instructions:
- Load the Iris dataset using scikit-learn.
- Preprocess the data (split into training and testing sets).
- Train a classification model using a suitable algorithm.
- Evaluate the model and make predictions on new data.
License:
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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