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🧠 AI Tools Assignment – Mastering the AI Toolkit

Authors: Nwokike Onyeka, Obinwa Ogechi Perpetual
Course: AI Tools and Applications
Institution: [Power Learn Project Academy]
Date: October 2025

Live URL

📘 Project Overview

This repository contains my complete submission for the AI Tools Assignment on the theme “Mastering the AI Toolkit.”
The project demonstrates understanding and practical use of modern AI frameworks — TensorFlow, PyTorch, Scikit-learn, and spaCy — across theory, implementation, and ethics.

🧩 Assignment Structure

Part Description Deliverable
Part 1 Theoretical Understanding of AI tools Theoretical_Answers.md
Part 2 – Task 1 Classical ML using Scikit-learn (Iris Classifier) Iris Classifier Notebook
Part 2 – Task 2 Deep Learning using TensorFlow (MNIST CNN) MNIST CNN Notebook
Part 2 – Task 3 NLP using spaCy (Entity & Sentiment Extraction) NLP Task
Part 3 Ethical Analysis and Reflection Ethical_Reflection.md

🧠 Tools & Frameworks Used

  • TensorFlow – for deep learning and CNN model building.
  • Scikit-learn – for classical machine learning (Decision Tree Classifier).
  • spaCy – for NLP tasks like Named Entity Recognition and Sentiment Analysis.
  • Jupyter Notebook / Google Colab – for experimentation and visualization.
  • GitHub – for version control and project submission.

🧪 Results Summary

Iris Classifier

  • Algorithm: Decision Tree Classifier
  • Accuracy: ~97%
  • Evaluation Metrics: Accuracy, Precision, Recall

MNIST CNN

  • Model: Convolutional Neural Network
  • Test Accuracy: >99%
  • Output: Classification of handwritten digits (0–9)

NLP with spaCy

  • Task: Named Entity Recognition and Rule-Based Sentiment Analysis
  • Entities Extracted: Product Names, Brands
  • Sentiment Output: Positive / Negative summary

⚖️ Ethical Reflection Summary

This project emphasizes responsible AI use — addressing bias, fairness, transparency, privacy, and human accountability.
See the full write-up: Ethical_Reflection.md

🏁 Final Notes

This project demonstrates the practical application of AI frameworks in machine learning, deep learning, and NLP — combined with ethical awareness.
It fulfills all parts of the AI Tools Assignment and serves as a foundation for future AI engineering projects.

💡 “Small wins lead to big successes — test code incrementally and think ethically.”