ai-tools-task1-iris

🌼 AI Tools Assignment – Task 1: Iris Species Classifier

This repository contains the implementation of a Decision Tree Classifier using Scikit-learn to classify iris flower species based on petal and sepal measurements. The notebook walks through dataset exploration, model training, evaluation, and basic data visualization.

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📁 Folder Structure

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🧪 Technologies Used

• Python 3.10+
• Scikit-learn
• Pandas
• Matplotlib
• spaCy (NER + sentiment example)
• Jupyter Notebook / VS Code

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📊 Tasks Covered

• Dataset loading and preprocessing
• Decision Tree training with Scikit-learn
• Model evaluation using classification report
• Visualization: scatter plot + decision tree diagram
• Named Entity Recognition (NER) and basic sentiment analysis
• Ethical reflection and theoretical questions

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📄 Submission Notes

This repo was prepared as part of the AI Tools Assignment for the **Power Learn Project

Academy (Feb 2025, Cohort VII)**.

📎 A detailed PDF report (Task_1_Short_Answers_Leonard.pdf) is included with:

• Answers to short theory questions
• Ethical reflection on AI model usage
• Screenshots of model outputs (classification report, NER, sentiment)

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✅ Author

Leonard Phokane
Power Learn Project | Academy – Software Development Cohort VII
Date: June 2025 📧 Email: leonardphokane1@gmail.com 🔗 GitHub: https://github.com/leonardphokane

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📬 Feedback & Contributions

Pull requests and feedback are welcome if you’re exploring similar decision tree projects or looking to learn Scikit-learn basics!

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