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> Practical Guide to Text Mining and Feature, Engineering in R
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Дата 22.07.2019 17:50
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Practical Guide to Text Mining and Feature Engineering in R
Источник: https://www.hackerearth.com/fr/practice/mac...ing-r/tutorial/

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Introduction

The ability to deal with text data is one of the important skills a data scientist must posses. With advent of social media, forums, review sites, web page crawlers companies now have access to massive behavioural data of their customers.

Yes, companies have more of textual data than numerical data. No doubt, this data will be messy. But, beneath it lives an enriching source of information, insights which can help companies to boost their businesses. That is the reason, why natural language processing (NLP) a.k.a Text Mining as a technique is growing rapidly and being extensively used by data scientists.

In the previous tutorial, we learnt about regular expressions in detail. Make sure you've read it.

In this tutorial, you'll about text mining from scratch. We'll follow a stepwise pedagogy to understand text mining concepts. Later, we'll work on a current kaggle competition data sets to gain practical experience, which is followed by two practice exercises. For this tutorial, the programming language used is R. However, the techniques explained below can be implemented in any programming language. 


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Дата 22.07.2019 17:51
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Table of Contents

    What is Text Mining (or Natural Language Processing ) ?
    What are the steps involved in Text Mining ?
    What are the feature engineering techniques used in Text Mining ?
    Text Mining Practical - Predict the interest level


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