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Update getting-started-with-github-codespaces-for-machine-learning.md (#35023)

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Co-authored-by: Alex Nguyen <150945400+nguyenalex836@users.noreply.github.com>
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Saipavan Lingamallu
2024-10-21 22:19:59 +05:30
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content/codespaces/developing-in-a-codespace/getting-started-with-github-codespaces-for-machine-learning.md
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@@ -34,7 +34,7 @@ A codespace for this template will open in a web-based version of {% data variab
### Opening the image classifier notebook ### Opening the image classifier notebook
The default container image that's used by {% data variables.product.prodname_github_codespaces %} includes a set of machine learning libraries that are preinstalled in your codespace. For example, Numpy, pandas, SciPy, Matplotlib, seaborn, scikit-learn, Keras, PyTorch, Requests, and Plotly. For more information about the default image, see "[AUTOTITLE](/codespaces/setting-up-your-project-for-codespaces/adding-a-dev-container-configuration/introduction-to-dev-containers#using-the-default-dev-container-configuration)" and the [devcontainers/images](https://github.com/devcontainers/images/tree/main/src/universal) repository]. The default container image that's used by {% data variables.product.prodname_github_codespaces %} includes a set of machine learning libraries that are preinstalled in your codespace. For example, Numpy, pandas, SciPy, Matplotlib, seaborn, scikit-learn, Keras, PyTorch, Requests, and Plotly. For more information about the default image, see "[AUTOTITLE](/codespaces/setting-up-your-project-for-codespaces/adding-a-dev-container-configuration/introduction-to-dev-containers#using-the-default-dev-container-configuration)" and the [devcontainers/images](https://github.com/devcontainers/images/tree/main/src/universal) repository.
1. In the {% data variables.product.prodname_vscode_shortname %} editor, close any "Get Started" tabs that are displayed. 1. In the {% data variables.product.prodname_vscode_shortname %} editor, close any "Get Started" tabs that are displayed.
1. Open the `notebooks/image-classifier.ipynb` notebook file. 1. Open the `notebooks/image-classifier.ipynb` notebook file.