Machine Learning Course Materials

This repository contains the course materials for ML1 (Introduction to Machine Learning) and ML2 (Advanced Machine Learning Concepts).

Project Structure

.
├── ml1/                    # Introduction to Machine Learning
│   └── lecture01/         # First lecture
│       └── textbook.md    # Lecture content in markdown
├── ml2/                    # Advanced Machine Learning
│   └── lecture01/         # First lecture
│       └── textbook.md    # Lecture content in markdown
├── output/                 # Generated PDFs (created by script)
├── generate_pdfs.py       # PDF generation script
└── requirements.txt       # Python dependencies

Setup

1. Install Python dependencies:

pip install -r requirements.txt

2. Install system dependencies:

• Pandoc
• TeX Live or MacTeX (for PDF generation)

Usage

To generate PDFs from markdown files:

python generate_pdfs.py

This will:

1. Check for required dependencies
2. Process all markdown files in ml1/ and ml2/
3. Generate PDFs in the output/ directory
4. Maintain course structure in output

Features

• Parallel processing for faster PDF generation
• Table of contents generation
• Math equation support
• Code syntax highlighting
• Consistent styling across documents
• Orange accent colors for links

Course Structure

ML1: Introduction to Machine Learning

• Fundamental concepts
• Basic mathematical foundations
• Simple model implementations

ML2: Advanced Machine Learning

• Advanced architectures
• Modern training techniques
• State-of-the-art implementations

Contributing

To add new lectures:

1. Create a new directory: mlX/lectureXX/
2. Add markdown content in textbook.md
3. Run the PDF generation script