Discovering Google Colab

Google Colaboratory, or Colab for short, is a cloud-based platform with many tools, including Colab Notebooks. Colab Notebooks are an amazing playground. They combine the power of Jupyter Notebooks with the accessibility and collaborative potential of Google Drive. Colab Notebooks are a free environment where anyone can write and execute Python code directly within their browser. They have a Secrets section to store API keys that keep them separate from your project. You can use markup and HTML to document your Notebooks. Installing new libraries in the virtual environment using the command line is very easy. This eliminates the need for complex installations and setups. There’s comprehensive documentation and many sample Colab Notebooks to learn from. It’s a convenient playground where you can experiment with Gemini’s API.

Some impressive features include:

• Powerful hardware: Colab allows you to use GPUs and TPUs for free to train and run complex LLMs that wouldn’t run on your local machine.
• Real-Time collaboration: You can share Notebooks and collaborate on them just like Google Drive documents.
• Preinstalled libraries: Many popular machine learning and data science libraries are preinstalled.
• Access the latest models: Try the latest AI and ML models and techniques without worrying about complex installations.
• Run code from GitHub: You can directly import and execute Jupyter notebooks from GitHub repositories.
• Visualize data: Create professional charts, graphs, and interactive visualizations within your notebooks.

The interface is simple to use. Colab Notebooks are a fantastic combination of power and simplicity.

Now that you’re familiar with Colab and its features, in the next demo, you’ll try samples provided for the Gemini API. You’ll also create a new Colab notebook.