Python AI Labs

This repository documents my structured learning and practical experiments in:

• Python programming
• Artificial Intelligence
• Machine Learning
• Data Processing
• Engineering-oriented problem solving

The goal is to build strong foundations in AI while maintaining an engineering mindset.

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🎯 Objectives

• Master Python fundamentals
• Understand data structures and algorithms
• Work with NumPy and Pandas
• Visualize data using Matplotlib
• Implement machine learning models
• Apply AI concepts to real engineering problems

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📂 Repository Structure

python-ai-labs/ │ ├── basics/ Python fundamentals ├── math/ Linear algebra & statistics ├── data/ Data processing experiments ├── ml/ Machine learning models ├── visualization/ Plots and data analysis └── README.md

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🧠 Learning Focus

This repository is focused on:

• Writing clean and structured code
• Understanding algorithms instead of copying models
• Building intuition behind ML concepts
• Connecting AI with embedded and control systems

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🔧 Technologies Used

• Python 3.x
• NumPy
• Pandas
• Matplotlib
• Scikit-learn

Future:

• PyTorch / TensorFlow
• Signal processing integration
• AI + Embedded systems

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🚀 Roadmap

Phase 1:

• Python fundamentals
• Math review (linear algebra, probability)

Phase 2:

• Supervised learning models
• Data preprocessing techniques

Phase 3:

• Neural networks
• Time-series and signal analysis

Phase 4:

• AI integration with hardware systems

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👨‍💻 Author

Electrical & Electronics Engineering Student
Embedded Systems • Control • AI Integration