🧠 Complete Beginner's Machine Learning Course

Welcome to the Complete Beginner's Machine Learning Course! This repository contains all the code, datasets, and lessons you need to master Machine Learning from scratch.

🚀 Getting Started

If you are new here, please start by reading the Introduction file to understand the core concepts of Machine Learning and the ML pipeline.

Course Structure

• introduction.md: The starting point of the course. Covers high-level ML concepts.
• datasets/: Contains the datasets used throughout the course (e.g., titanic.csv).
• python/data_prep.ipynb: Lesson 1. A comprehensive, beginner-friendly Jupyter Notebook teaching you the most important part of ML: Data Preparation (Cleaning, Feature Engineering, Imputation, and Scaling).

More Coming Soon...

🛠️ Environment Setup

To run the notebooks in this course locally, you will need Python installed.

1. Create a Virtual Environment:

   python -m venv .venv

2. Activate the Environment:
   • Windows: .\.venv\Scripts\Activate.ps1
   • Mac/Linux: source .venv/bin/activate
3. Install Required Libraries:

   pip install pandas numpy jupyter

4. Launch Jupyter: Open the notebooks directly in VS Code (with the Jupyter extension installed) or run jupyter notebook in your terminal.

📚 Future Content

This course is actively being developed. Future lessons will include Model Training, Evaluation, and building actual AI algorithms!