ML Tutorial

Welcome to the ML Tutorial repository! This repository contains resources, code, and explanations to help you learn Machine Learning (ML) using Python.

📌 Features

✅ Introduction to Machine Learning ✅ Hands-on Python implementations ✅ Step-by-step explanations ✅ Various ML algorithms with examples ✅ Jupyter notebooks for easy learning

📂 Folder Structure

📦 ML-tutorial
│── 📁 datasets/ # Sample datasets for practice
│── 📁 notebooks/ # Jupyter notebooks with code and explanations
│── 📁 models/ # Trained ML models (if any)
│── 📄 requirements.txt # Dependencies for the project
│── 📄 README.md # Project documentation

🚀 Getting Started

1️⃣ Clone the Repository

git clone https://github.com/nabeel03103n/ML-tutorial.git
cd ML-tutorial

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run Jupyter Notebook

jupyter notebook

Open the .ipynb files in the notebooks/ directory and start learning!

📚 Topics Covered

🔹 Introduction to ML 🔹 Data Preprocessing 🔹 Supervised Learning (Regression & Classification) 🔹 Unsupervised Learning (Clustering) 🔹 Feature Engineering 🔹 Model Evaluation & Optimization 🔹 Neural Networks (Basic Overview)

🤝 Contributing

Feel free to contribute by adding new notebooks, improving explanations, or fixing issues. Fork the repo and submit a pull request!

📧 Contact

For any queries, reach out to Nabeel Ali Khan: 📩 Email: nabeel.ali.private@gmail.com 📷 Instagram: nabeelalikhan_