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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.
Colab notebooks allow you to combine executable code and rich text in a single document, along with images, HTML, LaTeX and more. When you create your own Colab notebooks, they are stored in...
The goal of this Colab notebook is to highlight some benefits of using Google BigQuery and Colab together to perform some common data science tasks. Online prediction with BigQuery ML
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.
With Colab you can import an image dataset, train an image classifier on it, and evaluate the model, all in just a few lines of code. Colab notebooks execute code on Google's cloud servers,...
Whether you’re an ML expert or you’re just getting started, you’ll find training and information in our resource center. Learn with Google AI. At Google, we think the impact of AI will be most powerful when everyone can use it. Explore our tools.
Official Colab Help Center where you can find tips and tutorials on using Colab and other answers to frequently asked questions.
In order to provide access to as many students and under-resourced groups around the world as possible, Colab prioritizes users who are actively programming in a notebook. Colab also restricts...
Colab provides automatic completions to explore attributes of Python objects, as well as to quickly view documentation strings. As an example, first run the following cell to import the numpy...