Jupyter Notebook vs Google Colab – Best Tools to Write ML Code

📓 Lesson 2: Using Jupyter Notebooks & Google Colab

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Want to write and run Python code for Machine Learning without setting up anything complicated? In this lesson, you’ll learn how to use Jupyter Notebooks and Google Colab — the two most popular tools for ML development.

💻 What is Jupyter Notebook?

Jupyter Notebook is an open-source web app where you can write Python code, run it, and document it — all in one place. Great for data science and ML projects.

Run Python in cells (code blocks)
Add notes and explanations (Markdown)
Visualize data right below your code

🌐 What is Google Colab?

Google Colab is like Jupyter Notebook on the cloud. It’s free, runs in your browser, and lets you use GPU/TPU for ML models — without installation!

No setup needed — works with your Google Drive
Run code, install libraries, and share notebooks easily
Use GPU/TPU for faster model training (optional)

Feature	Jupyter Notebook	Google Colab
Setup	Install manually (Anaconda/Pip)	No setup, runs in browser
Speed Boost	CPU only	GPU/TPU (Free)
Collaboration	Manual sharing	Easy sharing with Google Drive

🧪 Try It Now:

👉 Open this sample notebook on Google Colab and try writing a simple Python program:

print("Hello, ML World!")

📝 Self-Check

Which tool requires installation: Jupyter or Colab?
How can Google Colab help students without powerful laptops?
Can you share your notebook with a classmate using Colab?

👉 Up next: Learn about **Pandas & NumPy** — your tools for working with real-world datasets in Python.

Machine Learning with Python: From Basics to Capstone

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