Welcome to Google Colab
Google Colab, or "Colaboratory," is a free cloud service hosted by Google, based on Jupyter Notebooks, that allows anyone to write and execute arbitrary Python code through the browser. Colab is especially well suited for machine learning, data analysis, and education, largely because of its ease of use and collaboration features.
This is the intro video from the Colab team: https://youtu.be/rNgswRZ2C1Y?si=STJnSKU3y8YO14aQ
Some key features and aspects of Google Colab are like below.
No Setup Required
Perhaps one of Colab's biggest attractions is that it requires no setup to use. You can write and execute Python code, create and share documents, while the environment handles all the installations and setup for you.
Free Access to GPUs and TPUs
Google Colab provides free access to hardware accelerators like GPUs and TPUs to run computationally intensive tasks. This is particularly beneficial for tasks in machine learning and deep learning, which require significant computational power.
Just like Google Docs, Colab notebooks can be shared, allowing for real-time collaboration with colleagues or friends. You can comment, edit, and work together on the same document.
Integration with Google Drive
Colab is integrated with Google Drive. It allows you to save your work directly to your Google Drive, share your work with others, access it from anywhere, and even mount your Drive to your Colab environment.
Supports External Data
Colab allows you to load data easily from various sources including your local system, Google Drive, GitHub, and others. It supports various data science libraries (like Pandas, NumPy, Matplotlib) and machine learning frameworks (like TensorFlow, PyTorch, and Keras) that you can use to analyze and visualize your data.
It's widely used for educational purposes since it allows tutors and learners to write and execute code in shared notebooks, making it an excellent tool for teaching coding and data science.
Google Colab provides a Jupyter notebook environment that runs entirely in the cloud. It generally offers a stable version of Python (often Python 3.x) and allows you to install other libraries using pip.
While Colab is powerful, it has some limitations. The session durations are limited (runtime resets after a period of inactivity), and while GPU and TPU access is free, it's provided on a "first come, first served" basis with usage limits. For more persistent usage or greater computational needs, Google offers Colab Pro with more resources.