This repository contains a collection of 10 practical projects built using Python and NumPy as part of a structured learning and revision phase for Artificial Intelligence, Machine Learning, NLP, and Deep Learning.
This is not a beginner starting point — it is a mastery phase focused on strengthening core concepts through real-world problem solving.
Each project targets a specific concept of NumPy that is essential for machine learning.
| # | Project Name | Concept |
|---|---|---|
| 1 | Student Marks Analyzer | Data analysis |
| 2 | Dice Simulator | Probability |
| 3 | Random Password Generator | Random sampling |
| 4 | Random Data Generator | Data simulation |
| 5 | Image to Grayscale | Image processing |
| 6 | Weather Data Analyzer | Time-series analysis |
| 7 | Matrix Calculator | Linear algebra |
| 8 | Checkerboard Generator | Vectorization |
| 9 | Game Leaderboard Analyzer | Ranking & sorting |
| 10 | Monte Carlo Pi | Simulation & probability |
- NumPy arrays and operations
- Vectorization (no loops mindset)
- Linear algebra (
numpy.linalg) - Random data generation
- Statistical analysis
- Simulation techniques
- Image processing basics
To build a strong foundation in NumPy, which is essential for:
- Machine Learning
- Data Science
- Deep Learning
- NLP
Muhammad Hanzlah
AI Engineer in Progress 🚀
Consistency beats intensity.
This repository represents continuous effort toward mastering the fundamentals required for advanced AI development.