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Natural Language Processing Experiments

Welcome to the Natural Language Processing (NLP) Experiments repository! This repository contains a collection of projects and resources designed to help you explore and understand various NLP techniques and concepts using Python.

Table of Contents

Basic Corpus Analysis

This project involves basic analysis of a text corpus, including frequency distribution, word cloud generation, and more.

  • Folder: Basic_Corpus_Analysis
  • Contents: Scripts and notebooks for analyzing text corpora

Bigram Table

Generate and analyze bigram tables to understand word pair frequencies within a corpus.

  • Folder: Bigram_Table
  • Contents: Scripts and notebooks for creating and analyzing bigram tables

Constituency Parsing

Explore constituency parsing techniques to understand the syntactic structure of sentences.

  • Folder: Constituency_Parsing
  • Contents: Scripts and examples for performing constituency parsing

Naive Bayes Text Classification

Implement Naive Bayes algorithms for text classification tasks, including sentiment analysis and spam detection.

  • Folder: Naive_Bayes_Text_Classification
  • Contents: Notebooks and scripts for Naive Bayes text classification

Named Entity Recognition

Identify and classify named entities in text using various NLP techniques.

  • Folder: Named_Entity_Recognition
  • Contents: Scripts and notebooks for performing named entity recognition

POS Tags Using Viterbi

Implement the Viterbi algorithm to assign part-of-speech (POS) tags to words in a sentence.

  • Folder: POS_Tags_Using_Viterbi
  • Contents: Scripts and examples using the Viterbi algorithm for POS tagging

POS Using Hidden Markov Model

Use Hidden Markov Models (HMMs) to perform part-of-speech tagging on text data.

  • Folder: POS_Using_Hidden_Markov_Model
  • Contents: Notebooks and scripts for POS tagging using HMMs

Project on Translator

Develop a translator project to convert text from one language to another using NLP techniques.

  • Folder: Project
  • Contents: Scripts, notebooks, and resources for building a language translator

Stemmer vs Lemmatizer

Compare stemming and lemmatization techniques to preprocess text data effectively.

  • Folder: Stemmer_vs_Lemmatizer
  • Contents: Scripts and notebooks comparing stemmers and lemmatizers

License

This repository is licensed under the MIT License. See the LICENSE file for more details.

Contact

If you have any questions or feedback, please reach out to us at desicoder14@gmail.com.

Happy Experimenting!