Learn GOOGLE-COLAB with Real Code Examples

Web interface built with JavaScript, HTML, and CSS

Python kernel runs in Google-managed cloud environment

Notebook files (.ipynb) stored in Google Drive or temporary VM storage

Cells executed in order with access to cloud resources

GPU/TPU accessed via Google Colab runtime settings

Notebook interface built with JavaScript/HTML/CSS

Python kernel runs in Google-managed cloud VM

Cells executed interactively with output rendered inline

GPU/TPU accessed via cloud runtime selection

Notebooks stored in Drive or temporary VM storage

Client-server model with browser front-end

Cloud-executed Python kernel

Separation of code, markdown, and output

Event-driven execution on cell run

Real-time collaboration supported via Google Drive

Data science projects and ML pipelines

Research collaboration in academia

Interactive tutorials and online courses

Prototyping models with GPU/TPU

Visualizing and analyzing datasets in-browser

Cloud-first, no local setup required

Interactive and notebook-based coding

Supports Python and ML workflows

Easy sharing and collaboration

Access to free compute acceleration for experimentation

Small: single scripts or experiments

Medium: multi-cell analysis workflows

Large: full ML pipelines with datasets

Enterprise: integrate with Google Cloud resources

Global: accessible to anyone with a browser and internet

Download notebook for local Jupyter use

Upload local notebooks to Colab

Install missing packages using pip

Adjust runtime to match local environment

Use Colab for prototyping before full deployment