Introduction to Google Colab: What is it and Why Use it?

In simple terms, Google Colab is an online platform that allows you to create, run, and collaborate on Jupyter notebooks in the cloud. But what exactly does that mean?

To understand the significance of Colab, let’s first define what a Jupyter notebook is. A Jupyter notebook is an interactive environment where you can write and execute code, visualize data, and share your work with others. It’s like having a digital whiteboard where you can scribble notes, equations, and code snippets, all in one place.

Google Colab takes this concept to the next level by providing a cloud-based platform for creating and collaborating on Jupyter notebooks. This means that you can access powerful computing resources from anywhere, at any time, without having to worry about provisioning or configuring infrastructure.

There are a few key differences that set Colab apart from other cloud-based access to powerful computing resources:

• Hassle-free Starting Up: It does not require any initial setup or installation, you can get started by simply going to colab.research.google.com and signing in to your Google Account.
• Access to Powerful Hardware: You can start working on your projects immediately, without the need to provision or configure any infrastructure. This means that you can start experimenting with code and data right away, without having to wait for resources to become available.
• Collaboration Features: Allows for seamless collaboration with others, making it easy to work with teams and share knowledge via Google Sharing. This is especially useful when working on complex projects that require input from multiple stakeholders.
• It’s Free: Unlike SageMaker and Cloud AI Platform, which require a paid subscription for most features, Colab is completely free. This makes it an attractive option for individuals or small teams looking to dip their toes into the world of machine learning.
• Accessibility: Since Figma is web-based, there’s no need to download or install any software. You simply need to visit figma.com, sign up for a free account, and you can start designing right away.

So, what are the benefits of using Google Colab?

• No setup required: You don’t need to install any software or configure anything – just create a Google account and start using Colab.
• Free Computing Resources: With Colab, you can tap into the power of Google’s cloud infrastructure without breaking the bank. This means that you can focus on developing your skills and building your projects, rather than worrying about the cost of computing resources.
• Collaboration Made Easy: Share your work with colleagues and collaborators across the globe, all from one platform. This makes it easy to work on team projects, share knowledge, and get feedback in real-time.
• Integration with other Google tools: Colab integrates well with other Google tools like Google Sheets, Google Drive, and Google Docs, making it easy to incorporate data and insights from these services into your notebooks.
• Instant Feedback: Run experiments and iterate on your models quickly, thanks to Colab’s instant compute capabilities. This means that you can test and refine your code rapidly, without having to wait for results or worry about the cost of computing resources.
• Easy deployment: Once you’ve developed a model or code in Colab, you can easily deploy it to production using Google Cloud’s AI Platform or other services.

Here are how you can set up a notebook in Google Colab:

1. Head to colab.research.google.com.
2. Sign in into your Google account.
3. Click on the “New Notebook” button.
4. Choose from various templates or you can start from scratch.

This opens up a blank notebook with code cells (for Python code) and text cells (for writing in Markdown). You’re now ready to write code and run AI experiments directly in the cloud.

If you are following along, then great! You have your notebook set up. Let’s try and write some simple Phyton code:

print(“Hello, World!”)

Click the play button beside the cell, or press Cmd+Enter (Mac) / Ctrl+Enter (Windows/ Linux). The output:

Hello, World!

Congrats—you’ve just executed your first Python cell in Colab! This real-time interactivity is perfect for training AI models, running marketing data scripts, or even just learning the basics of Python.

One of the most powerful features of Google Colab is its ability to install libraries using pip. In this example let’s try to install TensorFlow.

1. Input the following code
   
!pip install tensorflow
2. Run the code.
3. You should be able to see that the installation process is now complete.

Once installed, you can import and use them like you would in any local environment—only now, you’re running in the cloud with powerful hardware.

Colab isn’t just about code—it also supports interactive charts using libraries like Altair, Matplotlib, or Plotly. Plus, you can write clean documentation using Markdown to add explanations, formulas, and headings between code cells.
Perfect for:

• Annotating your machine learning pipeline
• Explaining data insights to non-technical teammates
• Creating AI reports or marketing dashboards

Google Colab is more than just a notebook—it’s an accessible gateway into the world of AI, NLP, and data science. Whether you’re training machine learning models, analyzing marketing campaigns, or just testing out ideas, Colab provides a fast, free, and flexible environment to bring your projects to life.

Coming up next: We’ll show you how to import a Hugging Face model using Colab for sentiment analysis in marketing.