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Colab is a free cloud service that lets you create and share interactive notebooks with code, text, and visualizations. You can use Colab for data science, machine learning, and access to Gemini models created by Google DeepMind.
- Notebook
Notebook - Google Colab
- Getting Started
Colab notebooks allow you to combine executable code and...
- Importing Libraries and Installing Dependencies
To import a library that's not in Colaboratory by default,...
- Sign In
Sign in to Google Classroom to access and manage your...
- Interactive Widgets
This notebook demonstrates use of Colab's layout widgets....
- TensorFlow With TPUs
TensorFlow With TPUs - Google Colab
- Overview of Colaboratory
Colab provides automatic completions to explore attributes...
- Charts
Charts - Google Colab
- Notebook
Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education.
Explore various topics and learn how to use Google Colab for data science, machine learning, AI, and more. Find notebooks on Gemini API, music transcription, text classification, TensorBoard, and more.
Learn how to use Colaboratory, a web-based notebook for executing Python code and viewing rich outputs. Explore features such as cells, magics, completions, exceptions, and integration with Google Drive.
Colab is a free cloud service that lets you create and share interactive notebooks with code, text, and visualizations. You can use Colab for data science, machine learning, and access to Gemini models created by Google DeepMind.
Oct 18, 2022 · Learn how to use Google Colab, a free Jupyter notebook that allows to run Python in the browser with pre-installed libraries and GPUs. Find out how to install packages, run magic commands, connect to Google Drive, and more.
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10 Minutes to Pandas — in Colab! Pandas is a popular open source Python package for data science, data engineering, analytics, and machine learning. It’s built on top of NumPy, which provides efficient support for numerical computation on multi-dimensional arrays.