Bem_vindo_ao_Colaboratory.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Bem vindo ao Colaboratory",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sclaudiobr/algoritmos-py/blob/master/Bem_vindo_ao_Colaboratory.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "5fCEDCU_qrC0"
      },
      "source": [
        "<p><img alt=\"Colaboratory logo\" height=\"45px\" src=\"https://colab.research.google.com/img/colab_favicon.ico\" align=\"left\" hspace=\"10px\" vspace=\"0px\"></p>\n",
        "\n",
        "## Bem-vindo ao colaborativo! **\n",
        "\n",
        "O Collaboratory é um ambiente de notebook gratuito da Jupyter que não requer configuração e é executado inteiramente na nuvem.\n",
        "\n",
        "Com o Collaboratory você pode escrever e executar código, salvar e compartilhar suas análises e acessar poderosos recursos de computação, tudo gratuitamente no seu navegador. Para ver a tradução do vídeo click na opção \"Habilitar legenda, Detalhes > Legenda(CC) > Traduzir automaticamente > Portugues \"."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "xitplqMNk_Hc",
        "outputId": "55ee29e9-f151-464f-e55d-5be94b4f6a62",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        }
      },
      "source": [
        "#@title Introdução ao Colaboratory { display-mode: \"form\" }\n",
        "#@markdown Este video de 3-minutos apresenta um panorama das propriedades chaves do Colaboratory:\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('inN8seMm7UI', width=600, height=400)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"600\"\n",
              "            height=\"400\"\n",
              "            src=\"https://www.youtube.com/embed/inN8seMm7UI\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f75f6723518>"
            ],
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aM/hfGshRH9qmyDHHJhm4rXXSZJ8r8uWEYFJD1Qi53VAyUeGWh3XcXqxS91vG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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "GJBs_flRovLc"
      },
      "source": [
        "## Vamos começar\n",
        "\n",
        "O documento que você está lendo é um [caderno Jupyter] (https://jupyter.org/), hospedado em Colaboratory. Não é uma página estática, mas um ambiente interativo que permite escrever e executar código no Python e em outros idiomas.\n",
        "\n",
        "Por exemplo, aqui está uma ** célula de código ** com um script Python curto que calcula um valor, armazena-o em uma variável e imprime o resultado:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "gJr_9dXGpJ05",
        "outputId": "6e039e63-001e-40ed-e9b6-ac416429fac6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "segundos_no_dia = 24 * 60 * 60\n",
        "segundos_no_dia"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "86400"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "2fhs6GZ4qFMx"
      },
      "source": [
        "Para executar o código na célula acima, selecione-o com um clique e pressione o botão play à esquerda do código ou use o atalho de teclado \"Command / Ctrl + Enter\".\n",
        "\n",
        "Todas as células modificam o mesmo estado global, portanto, variáveis ​​que você define executando uma célula podem ser usadas em outras células:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "-gE-Ez1qtyIA",
        "outputId": "482bc299-f592-4cd6-a5e1-7d84c17cfa46",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "segundos_na_semana = 7 * segundos_no_dia\n",
        "segundos_na_semana"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "604800"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "lSrWNr3MuFUS"
      },
      "source": [
        "Para obter mais informações sobre como trabalhar com blocos de notas de colaboração, consulte [Visão geral do colaborador] (/ notebooks / basic_features_overview.ipynb).\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "-Rh3-Vt9Nev9"
      },
      "source": [
        "## Mais recursos\n",
        "\n",
        "Aprenda como aproveitar ao máximo as ferramentas relacionadas a Python, Jupyter, Colaboratory e relacionadas com esses recursos:\n",
        "\n",
        "### Trabalhando com Notebooks em Colaboratory\n",
        "- [Visão Geral do Colaboratório](https://colab.research.google.com/notebooks/basic_features_overview.ipynb)\n",
        "- [Guia para o Markdown](https://colab.research.google.com/notebooks/markdown_guide.ipynb)\n",
        "- [Importando bibliotecas e intalando dependências](https://colab.research.google.com/notebooks/snippets/importing_libraries.ipynb)\n",
        "- [Salvando e carregando notebooks no GitHub](https://colab.research.google.com/github/googlecolab/colabtools/blob/master/notebooks/colab-github-demo.ipynb)\n",
        "- [Formulários interativos](https://colab.research.google.com/notebooks/forms.ipynb)\n",
        "- [Widgets interativos](https://colab.research.google.com/notebooks/widgets.ipynb)\n",
        "\n",
        "### Trabalhando com dados\n",
        "- [Carregando dados do: Gdrive, Sheets, e Google Cloud Storage](https://colab.research.google.com/notebooks/io.ipynb) \n",
        "- [Charts: visualizando os dados](https://colab.research.google.com/notebooks/charts.ipynb)\n",
        "- [Começando com BigQuery](https://colab.research.google.com/notebooks/bigquery.ipynb)\n",
        "\n",
        "### Curso Aprendizado de Aprendizado de Máquina\n",
        "Estes são alguns dos cadernos do curso on-line Machine Learning do Google. [full course website](https://developers.google.com/machine-learning/crash-course/) para mais informações.\n",
        "- [Introdução ao Pandas](https://colab.research.google.com/notebooks/mlcc/intro_to_pandas.ipynb)\n",
        "- [Conceitos de Tensorflow](https://colab.research.google.com/notebooks/mlcc/tensorflow_programming_concepts.ipynb)\n",
        "- [Primeiros passos com TensorFlow](https://colab.research.google.com/notebooks/mlcc/first_steps_with_tensor_flow.ipynb)\n",
        "- [Introdução às redes neurais](https://colab.research.google.com/notebooks/mlcc/intro_to_neural_nets.ipynb)\n",
        "- [Introdução a dados esparsos e inserções](https://colab.research.google.com/notebooks/mlcc/intro_to_sparse_data_and_embeddings.ipynb)\n",
        "\n",
        "### Usando Aceleradores de Hardware (GPU/TU)\n",
        "- [TensorFlow com GPUs](https://colab.research.google.com/notebooks/gpu.ipynb)\n",
        "- [TensorFlow com TPUs](https://colab.research.google.com/notebooks/tpu.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "P-H6Lw1vyNNd"
      },
      "source": [
        "## Exemplos de aprendizado de máquina: Seedbank\n",
        "\n",
        "Para ver exemplos de ponta a ponta das análises interativas de aprendizado de máquina que o Colaboratory possibilita, confira o projeto [Seedbank] (https://research.google.com/seedbank/).\n",
        "\n",
        "Alguns exemplos apresentados:\n",
        "\n",
        "- [Transferência de estilo neural] (https://research.google.com/seedbank/seed/neural_style_transfer_with_tfkeras): use o aprendizado profundo para transferir o estilo entre as imagens.\n",
        "- [EZ NSynth] (https://research.google.com/seedbank/seed/ez_nsynth): sintetize o áudio com os codificadores automáticos WaveNet.\n",
        "- [MNIST de moda com Keras e TPUs] (https://research.google.com/seedbank/seed/fashion_mnist_with_keras_and_tpus): Classifique imagens relacionadas à moda com aprendizado profundo.\n",
        "- [DeepDream] (https://research.google.com/seedbank/seed/deepdream): produza imagens do DeepDream a partir de suas próprias fotos.\n",
        "- [VAE Convolucional] (https://research.google.com/seedbank/seed/convolutional_vae): Crie um modelo generativo de dígitos manuscritos."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_-YmU3zBvE__",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}