Programming for Machine Learning and Business

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This repository contains the source code and materials for the Python for Machine Learning and Business JupyterBook.
It is designed to teach Python fundamentals, data science, algorithms, and business-focused ML applications through interactive notebooks, exercises, and real case studies.

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Features

• Complete Python + Business ML curriculum
• Hands-on Jupyter Notebooks
• Interactive execution in:
  • JupyterLite (runs in browser, no setup)
  • Google Colab
  • Local Jupyter environment
• Covers fundamentals → advanced → deployment

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How to Build Locally

# 1. Clone the repo
git clone https://github.com/chandraveshchaudhari/Programming_for_Business.git
cd Programming_for_Business

# 2. Install dependencies
pip install -r requirements.txt

# 3. Build the JupyterBook
jupyter-book build .

# 4. Preview in browser
open _build/html/index.html

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Contents Overview

• Python Fundamentals
• Data Wrangling and Visualization
• Algorithms and Data Structures
• Object-Oriented Programming with Case Studies
• Business Data Formats (Excel, APIs, PDFs)
• Advanced Python (Concurrency, Web Scraping, Automation)
• Database Integration (SQL & NoSQL)
• Bash Scripting for Automation
• Cloud Deployment (Docker, Kubernetes)
• Capstone Project

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Contributing

Contributions are welcome! If you’d like to fix errors, improve explanations, or add new exercises:

1. Fork the repo
2. Create a feature branch
3. Submit a pull request

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Features of This Book

• Interactive Book built with JupyterBook
• In-browser execution via JupyterLite
• Colab badges to open notebooks directly in Google Colab
• Pre-configured GitHub Actions for automatic deployment to GitHub Pages
• Organized structure with content/files/ for notebooks, _config.yml, and _toc.yml already set up

👥 Contributors

Thanks to all the amazing people who have contributed to this project 💖

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👩‍🏫 About the Book Maintainer

Dr. Chandravesh Chaudhari

📧 chandraveshchaudhari@gmail.com 🌐 Website 🔗 LinkedIn

Get Started Now

• Use the sidebar (Table of Contents) to navigate through chapters.
• Try out the examples directly in JupyterLite or Google Colab.
• Customize the content and publish your own book.