Imagine a world where you can train a neural network, analyze petabytes of data, and run cutting-edge machine learning algorithms, all with just a few clicks and a web browser. This isn’t science fiction, it’s Google Colab, don’t know about Google Colab? New to Google Colab? Don’t worry, just keep reading the article.
So in this article, we’ll discuss and explore everything about Google Colab from its core points. We will cover topics like, what Google Colab is it, is Google Colab free, what are the features of Google Colab, and what are it’s limitations and how we can get started with Google Colab. So if you’re a beginner and have no knowledge about Google Colab, then this article will going to make you pro in this topic. By the end of this article, you will have complete knowledge of Google Colab, and you will be able to teach everyone. Now let’s understand Google Colab in our today’s title Google Colab: A Beginner’s Guide to Unleashing Your Data Science Potential.
What is Google Colab?
Google Colab, also know as Google Colaboratory, is a cloud-based Jupyter notebook environment that allows us to write and execute Python code directly in our web browser. No software installation is required, and we can access powerful computing resources, including GPUs and TPUs, for free. This makes Colab ideal for data science, machine learning, and scientific computing tasks, regardless of your personal computer’s capabilities.
Is Google Colab Free?
Yes, Google Colab is absolutely free and easy to use. But there is a requirement that, you should have an active Google account, as Google Colab is a product of Google, so only Google users can take the benefit of it. But there is a limitation in free version, Google Colab has a Paid version too, and there is less features in free version as compared to paid version. So if you need more powerful resources or longer runtime, you can upgrade to a paid Colab Pro plan.
What are the Features of Google Colab?
Google Collab has lots of features to use. But there’s a problem, that limited feature is available in free version, and all features are available in the paid version. For example, these are the features we get in free version:
1. Jupyter notebook interface
The Jupyter notebook interface is an interactive environment for working with code, data, and visualizations. It combines code execution, rich text, and visualization in a single document, making it a popular tool for data science, scientific computing, and machine learning.
2. GPUs and TPUs
The Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs) both are accelerators of Google Colab. Both significantly speed up the computation of any running process. For example, GPUs are good at handling various tasks, including graphics processing, scientific computing, and deep learning. Where as TPUs are used for machine learning tasks, specifically optimized for TensorFlow.
3. Pre-installed libraries
The free version of Google Colab comes with pre-installed libraries with a vast arrays and frameworks commonly used in data science, machine learning, and scientific computing. For example: NumPy, Pandas, SciPy, TensorFlow, PyTorch etc.
4. Mount Drive Access
As Google Colab and Google Drive both are products of Google, so Google Colab also provides the facility to save notebooks and codes in the users of Google Drive. Google users can import files or code to Google Colab directly with a option “Mount Drive” without uploading any code manually to Google Colab.
5. Code Execution Access
This is the best feature of Google Colab, that we don’t need to host our code in any external platform, even we don’t need to buy any hosting or virtual private server for terminal or shell access to run or execute the code. Google Colab provides it’s users to freely host the code in the Google Colab notebook and run without any terminal.
What are the Limitations of Google Colab?
As already told in the beginning, that Google Colab comes with a paid version too that is known as Google Colab Pro plan. Google Colab doesn’t gives much benefits in free version as it gives in the paid version. For example:
1. Free resources are limited
While you can occasionally grab a GPU or TPU, they’re not guaranteed and sessions might be interrupted. Expect longer execution times for CPU-bound tasks.
2. Limited session timeouts
Free sessions automatically time out after 12 hours, requiring you to restart your notebook and potentially losing progress.
3. No persistent disk
Changes made to your environment aren’t permanently saved in the free version. You need to mount Google Drive or cloud storage for persistent data.
4. Limited control over environment
You don’t have full control over the underlying infrastructure, making it less suitable for highly-sensitive or regulated projects.
5. Limited access to certain features
Advanced features like larger storage options and guaranteed access to specific hardware require paid Colab Pro subscriptions. Google Colab AI is also added recently, and it will be available only for Colab Pro plan users. Currently it’s available in the free version too for a certain time.
How to get Started with Google Colab? How can I get account?
Getting started with Google Colab is super easy and doesn’t require any account creation! See how you can do it, just follow our steps:
1. Accessing Google Colab
Open your web browser and Click Here or simply search for “Google Colab” in your browser. Then, You’ll land on the main page where you can see recent and recommended notebooks.
2. Creating a New Notebook
Then, click on the “New” button near the top left corner. After that, a dropdown menu will appear. Then, select “Colaboratory notebook” this will open a new blank notebook with the Jupyter interface. After that, You’ll see sections for code cells and output cells, along with a sidebar for exploring variables and other tools.
3. Writing and Running Code
In any code cell, start typing your Python code. You can experiment with simple examples like printing “Hello, Colab!” or using basic arithmetic functions. To execute the code, you have two options: Press the “Play” button (triangle symbol) located at the left edge of the code cell. Press the Shift + Enter keyboard shortcut. The output of your code will be displayed below the cell, showing the results of your calculations or any printed messages.
4. Exploring the Interface
Feel free to browse through the various menus and options available in the Colab interface. You can find many helpful options, such as: File menu, Edit menu, Insert menu, Kernel menu, Help menu etc.
5. Saving and Sharing your Work
Since you don’t need an account for basic use, your notebook is temporarily saved in your browser session. To keep it permanently: Click on “File” > “Save to Drive” to save the notebook in your Google Drive. Click on “File” > “Download notebook” to download a copy as a .ipynb file. You can also share your notebook with others by clicking on “File” > “Share” and generating a shareable link. This link will allow anyone with the link to view or edit your notebook, depending on your chosen permissions.
Google Colab presents an accessible and powerful platform for data scientists and machine learning enthusiasts, offering a cloud-based Jupyter notebook environment. Its free version provides essential features like Jupyter interface, access to GPUs and TPUs, pre-installed libraries, drive mounting, and code execution without external hosting. However, limitations such as limited resources, session timeouts, and restricted control over infrastructure exist in the free version, making the paid Colab Pro plan a consideration for those requiring more robust resources and features. Beginners can easily start harnessing Colab’s capabilities by following simple steps, exploring its interface, running Python code, and saving/sharing their work without the necessity of creating an account. Google Colab stands as a promising tool, unlocking the potential for individuals to delve into data science and machine learning with ease.
I hope this article will benifit you, and no points must have left. If you’re satisfied with the article, make sure to share your openion with us. And if you want to learn more about different Google products, then you can check our our “Google Products” category. We have published similar articles on Google products. And soon after explaining all Google products, we gonna publish it’s tutorial too. By the way, best of luck for your Google Colab journey, Thanks for reading till here!