Welcome to My-Machine-Learning-Learning-Curve 🚀
This repository is a collection of my personal journey in learning Machine Learning (ML).
The idea behind it was simple:
- Go online and find old ML codebases – some unfinished because of errors, others outdated but functional.
- Revive, update, or complete them while learning in the process.
- Mix in code-along projects from YouTube courses and random experiments I explored on my own.
The result? A patchwork of projects that reflect my growth curve as I learned, broke things, fixed them, and improved my understanding of ML step by step.
- 🔧 Fixed & Updated Projects → Old codebases brought back to life.
- 🎥 Course Code-Alongs → Projects I built while following YouTube tutorials.
- 💡 Learning Experiments → Small personal projects for practicing concepts.
- 🕰 Legacy Work → Early attempts (with all the quirks and mistakes intact).
- To document my journey as I transitioned from beginner-level projects into more structured ML learning.
- To serve as a reference for anyone facing similar challenges with old or broken code.
- To remind myself (and hopefully inspire others) that progress is not linear — it’s a curve.
- Browse through the folders – each represents a different project.
- Check the included notes or comments inside the code for context.
- Feel free to clone, tinker, and learn alongside my journey:
git clone https://github.com/your-username/My-Machine-Learning-Learning-Curve.git
cd My-Machine-Learning-Learning-Curve- Basic ML concepts
- Data preprocessing and cleaning
- Model training and evaluation
- Updating deprecated libraries to current versions
- Debugging and fixing errors in legacy code
This repo is not about polished production-ready ML systems. It’s about the process of learning, experimenting, failing, and improving. So if you’re learning ML too, I hope this helps you see that struggling with old, messy codebases is part of the curve.
Enjoy! ✨