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Natural Language Processing Recipes PDF Download

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By using a problem-solution approach, Implementation of Natural Language Processing applications with Python is very useful. In this book, let us take a look on the potential of text data. Text data is most used and covers a bulk of the unstructured data. In order to produce significant and actionable insights from text data, to unlock the potential of text data, we use Natural Language Processing coupled with machine learning and deep learning.

As we all know that machines and algorithms do not understand texts or characters, so the conversion of text data into machine language (like binary form) to perform any type of analysis on text data. The ability that is used to enable machines to understand and interpret the human language (text data) is known as Natural Language Processing.

Let us take a look on human language processing into machine understandable form, from this PDF, that is follows:

1. Extracting the Data

  • Introduction
  • Collecting Data
  • Problem
  • Solution
  • How It Works

2. Collecting Data from PDFs

  • Problem
  • Solution
  • How It Works

3. Collecting Data from Word Files

  • Problem
  • Solution
  • How It Works

4. Collecting Data from JSON

  • Problem
  • Solution
  • How It Works

5. Collecting Data from HTML

  • Problem
  • Solution
  • How It Works

6. Parsing Text Using Regular Expressions

  • Problem
  • Solution
  • How It Works

7. Handling Strings

  • Problem
  • Solution
  • How It Works

8. Scraping Text from the Web

  • Problem
  • Solution
  • How It Works

9. Exploring and Processing Text Data

10. Converting Text Data to Lowercase

  • Problem
  • Solution
  • How It Works

11. Removing Punctuation

  • Problem
  • Solution
  • How It Works

12. Removing Stop Words

  • Problem
  • Solution
  • How It Works

13. Standardizing Text

  • Problem
  • Solution
  • How It Works

14. Correcting Spelling

  • Problem
  • Solution
  • How It Works

15. Tokenizing Text

  • Problem
  • Solution
  • How It Works

16. Stemming

  • Problem
  • Solution
  • How It Works

17. Lemmatizing

  • Problem
  • Solution
  • How It Works

18. Exploring Text Data

  • Problem
  • Solution
  • How It Works





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