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 …

借助 Colab，您可以充分利用常用 Python 库的强大功能来分析和可视化数据。 下方的代码单元格使用 NumPy 生成一些随机数据，并使用 Matplotlib 可视化这些数据。

Colab 可讓你充分利用熱門 Python 程式庫的強大功能，對資料進行分析並以視覺化方式呈現。 下方的程式碼儲存格使用 numpy 來產生一些隨機性資料，並透過 matplotlib 將這些資料視覺化。

Colab ora offre funzionalità AI basate su Gemini. Il video seguente fornisce informazioni su come utilizzare queste funzionalità, indipendentemente dal fatto che tu sia un principiante o un esperto di …

Mira este video introductorio sobre Colab o descubre funciones de Colab que tal vez te hayas perdido para obtener más información, o bien comienza a usarlo a continuación.

Colab을 통해 인기 있는 Python 라이브러리를 최대한 활용하여 데이터를 분석하고 시각화할 수 있습니다. 아래 코드 셀에서는 Numpy 를 사용하여 임의의 데이터를 생성하고 매트플롯립 으로 이를 시각화합니다. …

To follow this tutorial, run the notebook in Google Colab by clicking the button at the top of this page. In Colab, connect to a Python runtime: At the top-right of the menu bar, select CONNECT.

To see end-to-end examples of the interactive machine learning analyses that Colab makes possible, check out these tutorials using models from TensorFlow Hub. A few featured examples:

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 module.

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