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InessaPawsonInessaPawson
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Move keyfeatures to a grid of cards
Moving keyfeatures to a grid of cards. This PR is a part of the ongoing work to adopt the styling from pydata-sphinx-theme where possible.
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‎content/en/_index.md

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---
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title:
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---
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{{< grid columns="1 2 2 3" >}}
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{{< card >}}
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title = 'Powerful N-dimensional arrays'
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body = '''
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Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Numerical computing tools'
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body = '''
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NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Open source'
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body = '''
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Distributed under a liberal [BSD license](https://github.com/numpy/numpy/blob/main/LICENSE.txt), NumPy is developed and maintained [publicly on GitHub](https://github.com/numpy/numpy) by a vibrant, responsive, and diverse [community](/community).
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Interoperable'
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body = '''
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NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Performant'
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body = '''
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The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Easy to use'
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body = '''
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NumPy's high level syntax makes it accessible and productive for programmers from any background or experience level.
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'''
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{{< /card >}}
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{{< /grid >}}

‎content/en/config.yaml

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alttext: Cheetah pose analysis
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url: /case-studies/deeplabcut-dnn
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keyfeatures:
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features:
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- title: Powerful N-dimensional arrays
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text: Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today.
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- title: Numerical computing tools
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text: NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more.
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- title: Open source
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text: Distributed under a liberal [BSD license](https://github.com/numpy/numpy/blob/main/LICENSE.txt), NumPy is developed and maintained [publicly on GitHub](https://github.com/numpy/numpy) by a vibrant, responsive, and diverse [community](/community).
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- title: Interoperable
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text: NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
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- title: Performant
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text: The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
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- title: Easy to use
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text: NumPy's high level syntax makes it accessible and productive for programmers from any background or experience level.
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tabs:
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title: ECOSYSTEM
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‎content/ja/_index.md

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---
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title:
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---
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{{< grid columns="1 2 2 3" >}}
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{{< card >}}
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title = '強力な多次元配列'
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body = '''
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NumPyの高速で多機能なベクトル化計算、インデックス処理、ブロードキャストの考え方は、現在の配列計算におけるデファクト・スタ>ンダードです。
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'''
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{{< /card >}}
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{{< card >}}
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title = '数値計算ツール群'
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body = '''
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NumPyは、様々な数学関数、乱数生成器、線形代数ルーチン、フーリエ変換などを提供しています。
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'''
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{{< /card >}}
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{{< card >}}
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title = '相互運用性'
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body = '''
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NumPyは、幅広いハードウェアとコンピューティング・プラットフォームをサポートしており、分散処理、GPU、疎行列ライブラリにも対
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応しています。
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'''
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{{< /card >}}
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{{< card >}}
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title = '高パフォーマンス'
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body = '''
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NumPyの大部分は最適化されたC言語のコードで構成されています。これによりPythonの柔軟性とコンパイルされたコードの高速性の両方
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を享受できます。
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'''
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{{< /card >}}
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{{< card >}}
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title = '使いやすさ'
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body = '''
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NumPyの高水準なシンタックスは、どんなバックグラウンドや経験を持つのプログラマーでも簡単に利用することができ、生産性を高め>ることができます。
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'''
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{{< /card >}}
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{{< card >}}
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title = 'オープンソース'
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body = '''
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NumPyは、寛容な[BSDライセンス](https://github.com/numpy/numpy/blob/main/LICENSE.txt)で公開されています。NumPyは活発で、互>いを尊重し、多様性を認め合う[コミュニティ](/ja/community)によって、 [GitHub](https://github.com/numpy/numpy)上でオープンに開発されていま
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す.
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'''
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{{< /card >}}
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{{< /grid >}}

‎content/ja/config.yaml

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img: /images/content_images/case_studies/deeplabcut.png
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alttext: チータの姿勢推定
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url: /ja/case-studies/deeplabcut-dnn
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keyfeatures:
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features:
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-
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title: 強力な多次元配列
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text: NumPyの高速で多機能なベクトル化計算、インデックス処理、ブロードキャストの考え方は、現在の配列計算におけるデファクト・スタンダードです。
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-
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title: 数値計算ツール群
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text: NumPyは、様々な数学関数、乱数生成器、線形代数ルーチン、フーリエ変換などを提供しています。
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-
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title: 相互運用性
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text: NumPyは、幅広いハードウェアとコンピューティング・プラットフォームをサポートしており、分散処理、GPU、疎行列ライブラリにも対応しています。
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-
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title: 高パフォーマンス
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text: NumPyの大部分は最適化されたC言語のコードで構成されています。これによりPythonの柔軟性とコンパイルされたコードの高速性の両方を享受できます。
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-
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title: 使いやすさ
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text: NumPyの高水準なシンタックスは、どんなバックグラウンドや経験を持つのプログラマーでも簡単に利用することができ、生産性を高めることができます。
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-
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title: オープンソース
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text: NumPyは、寛容な[BSDライセンス](https://github.com/numpy/numpy/blob/main/LICENSE.txt)で公開されています。NumPyは活発で、互いを尊重し、多様性を認め合う[コミュニティ](/ja/community)によって、 [GitHub](https://github.com/numpy/numpy)上でオープンに開発されています.
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tabs:
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title: NumPyのエコシステム
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section5: false

‎content/pt/_index.md

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---
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title:
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---
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{{< grid columns="1 2 2 3" >}}
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{{< card >}}
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title = 'Arrays n-dimensionais poderosas'
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body = '''
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Rápidos e versáteis, os conceitos de vetorização, indexação e broadcasting do NumPy são, na prática, o padrão em computação com arrays.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Ferramentas de computação numérica'
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body = '''
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O NumPy oferece um conjunto completo de funções matemáticas, geradores de números aleatórios, rotinas de álgebra linear, transformadas de Fourier, e mais.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Interoperabilidade'
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body = '''
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O NumPy suporta um grande número de plataformas de hardware e computação, e pode ser combinado com bibliotecas de computação com arrays esparsas, distribuidas ou em GPUs.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Alto desempenho'
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body = '''
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O núcleo do NumPy é feito de código otimizado em C. Experimente a flexibilidade do Python com a velocidade de código compilado.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Fácil de usar'
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body = '''
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A sintaxe de alto nível do NumPy torna-o acessível e produtivo para programadores de qualquer nível de experiência e formação.
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'''
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{{< /card >}}
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{{< card >}}
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title = 'Código aberto'
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body = '''
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Distribuido com uma [licença BSD](https://github.com/numpy/numpy/blob/main/LICENSE.txt) liberal, o NumPy é desenvolvido e mantido [publicamente no GitHub](https://github.com/numpy/numpy) por uma [comunidade](/pt/community) vibrante, responsiva, e diversa.
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'''
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{{< /card >}}
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{{< /grid >}}

‎content/pt/config.yaml

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img: /images/content_images/case_studies/deeplabcut.png
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alttext: Análise de pose de um guepardo
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url: /pt/case-studies/deeplabcut-dnn
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keyfeatures:
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features:
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-
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title: Arrays n-dimensionais poderosas
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text: Rápidos e versáteis, os conceitos de vetorização, indexação e broadcasting do NumPy são, na prática, o padrão em computação com arrays.
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-
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title: Ferramentas de computação numérica
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text: O NumPy oferece um conjunto completo de funções matemáticas, geradores de números aleatórios, rotinas de álgebra linear, transformadas de Fourier, e mais.
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-
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title: Interoperabilidade
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text: O NumPy suporta um grande número de plataformas de hardware e computação, e pode ser combinado com bibliotecas de computação com arrays esparsas, distribuidas ou em GPUs.
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-
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title: Alto desempenho
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text: O núcleo do NumPy é feito de código otimizado em C. Experimente a flexibilidade do Python com a velocidade de código compilado.
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-
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title: Fácil de usar
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text: A sintaxe de alto nível do NumPy torna-o acessível e produtivo para programadores de qualquer nível de experiência e formação.
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-
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title: Código aberto
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text: Distribuido com uma [licença BSD](https://github.com/numpy/numpy/blob/main/LICENSE.txt) liberal, o NumPy é desenvolvido e mantido [publicamente no GitHub](https://github.com/numpy/numpy) por uma [comunidade](/pt/community) vibrante, responsiva, e diversa.
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tabs:
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title: ECOSSISTEMA
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section5: false

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