Natural Language Processing with Python Training

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Natural Language Processing with Python Training is ideal for the professionals willing to flourish their career in developing an advanced UI. Focusing on the Natural Language Processing with Python Course, this is efficient enough for guiding the candidates on how to implement the intelligence in a better way and leverage the probabilistic data structures so that matrix can be generated easily and meta features can be added as well.

The Natural Language Processing with Python Course helps the candidates in:

  • Understanding the implementation procedure of the Natural Language Tool Kit
  • How to load as well as manipulate your own text data.
  • Analyze the situations to implement solutions such as sentiment analysis and classification techniques.
  • Understand how to formulate solutions to text based problems
  • Develop an understanding on Loops and Conditionals to apply the python efficiently
  • Get an in-depth understanding of windows setup
Target audience

The Natural Language Processing with Python online Training is ideal for the candidates, who want to get familiar with Natural Language Processing and is looking for a way to start.

Prerequisites

The Natural Language Processing with Python online Training is ideal for the candidates, who want to get familiar with Natural Language Processing and is looking for a way to start.

1. Setup

  • Windows Setup
  • OS X Setup

2. Python Refresher

  • Lists
  • Dictionaries
  • Loops and Conditionals
  • Functions

3. NLTK and the Basics

  • An Overview - The Natural Language Tool Kit
  • The Counting Text
  • Frequency Distribution
  • Conditional Frequency Distribution
  • Bigrams
  • Overview - Regular Expressions

4. Tokenization, Tagging, Chunking

  • An Overview- Tokenization
  • Normalizing
  • Part of Speech Tagging
  • Chunking
  • Named Entity Recognition

5. Custom Sources

  • Overview - Character Encoding
  • Text File
  • HTML
  • URL
  • CSV File
  • Exporting
  • NLTK Resources

6. Projects

  • An Introduction to Sentiment Analysis
  • About Basic Sentiment Analysis
  • Introduction to Gender Prediction
  • Introduction TF-IDF

7. Appendix

  • Additional NLP Resources
  • Learning Python

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