Text_Analysis_Template.ipynb

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  "metadata": {
    "colab": {
      "name": "Text Analysis Template.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/GopiMindgloer/Learning-ML/blob/master/Text_Analysis_Template.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "metadata": {
        "id": "jNUy5pSa44Rz",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#import liraries"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Qgu8LjZH5unB",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#import files"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "rPThjC5k514k",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#create dataframe"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "uY4P5RXm58-I",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "##Basic Feature Extraction\n"
      ]
    },
    {
      "metadata": {
        "id": "RDhx4PGCBV89",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#extract the number of words in each tweet using split function"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "VhRUWLLpBdy7",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#extract the number of characters in each tweet"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "6g8-nSxbBrKk",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#calculate the average word length in each tweet"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "dC6cwxO2BzEQ",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#calculate the number of stopwords in each tweet"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "4Nnek5HBCBtE",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#extract the number of special characters in each tweet"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "7UqN3sNGCQ8r",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#extract the number of nuerics in each tweet"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "ehiKD3euCYo5",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#extract the number of upper case letters in each tweet"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "RB1oehgaCdrb",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "##Basic Text Preprocessing"
      ]
    },
    {
      "metadata": {
        "id": "jI4ZgOaSCitO",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Convert the tweets into lower case"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "pyKpCrmOCuSA",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Remove all the punctuations"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Q6xfD8npCuXN",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#remove the stopwords"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "o7AGd9LiCudg",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#remove top 10 commonly occuring words"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "8Bf2OJsyCupR",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#remove least used words"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "tJXJ30raCubH",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#correct the spellings of each words"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "qvOYzi1MDRcM",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#tokenization"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "G5TbLFXRDRYn",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#stemming"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "MVtVkYqQDZ12",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#lemmatization"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "zZuxylxoDei1",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "##Advanced Text Preprocesing"
      ]
    },
    {
      "metadata": {
        "id": "410xdeptDhkq",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#N-grams"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "m0Rjf6yTDr7P",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Text Frequency"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "6HGRGBLWDsBv",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Inverse Document Frequency"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "KuGG5-7gDr_e",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Term Frequency - Inverse Docuent Frequency TF-IDF"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "hgX1QN-fDr2u",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Bag of Words"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "DytB5ZBREEB2",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Sentiment Analysis"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "LFjlMR6QEMHX",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "#Word Embeddings"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}