Welcome to my chill space for small machine learning projects 👨💻
This is where I build and upload mini-projects to practice new algorithms I learn — nothing crazy or massive, just pure hands-on learning vibes 🚀
✅ This repo is NOT for major projects — it's just my sandbox for learning and applying ML concepts as I go.
📌 Some of my other (bigger) ML projects live in separate repos. This one is for the small, focused stuff.
Whenever I learn a new algorithm, I try to apply it to a small real-world problem using real datasets (or toy ones).
Each folder here is basically like a “learning checkpoint.”
Some concepts covered (Or Less idk, it depends on what time you see this repo):
- 📈 Simple Linear Regression
- 📊 Logistic Regression
- 🌸 Classification (e.g. Iris dataset)
- 💀 Binary Classification (e.g. Titanic dataset)
- 🏠 Regression Problems (e.g. House Price Prediction)
- 🧹 Basic Data Cleaning & Preprocessing
- ⚖️ Model Evaluation (accuracy, R², etc.)
More coming as I keep learning and growing 💪
simple-ml-projects/
│
├── house-price-prediction/
│ ├── house\_price\_model.ipynb
│ └── README.md
│
├── iris-classification/
│ ├── iris\_model.ipynb
│ └── README.md
│
├── titanic-survival/
│ ├── titanic\_model.ipynb
│ └── README.md
│
└── README.md
Each folder contains:
- ✅ A Jupyter Notebook
- 📁 Clean code with comments
- 🧾 A mini README explaining the project
If you're also learning ML and want to see how basic algorithms are applied to real datasets, feel free to:
- 🧠 Explore the notebooks
- 🔍 Read through the code + markdowns
- 💡 Get inspiration for your own learning journey
This repo is a part of my journey into the world of ML 🌍 I’ll keep adding more projects as I learn new stuff — it’s all about getting your hands dirty and learning by doing 🧠🛠️
If you’re a beginner too, let’s connect and grow together 💬
Made with curiosity and coffee ☕ by Ammar Yasser