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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. 셀을 클릭하면 코드 수정을 바로 시작할 수 있습니다.
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.
If using Google Colab, store your key in 'Secrets' for persistent access across sessions (see [installation]( 08e845.555win5win.com/installation.html#google-colab)). Otherwise, `dna_client.create` can take the API key directly.
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 your Google Drive account.
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.
Title Overview of Colab Features Markdown Guide Charts in Colab External data: Drive, Sheets, and Cloud Storage Getting started with BigQuery Forms
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.
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:
Los cuadernos de Colab te permiten combinar código ejecutable y texto enriquecido en un mismo documento, además de imágenes, HTML, LaTeX y mucho más. Los cuadernos que creas en Colab se almacenan en tu cuenta de Google Drive.
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 your Google Drive account.
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