https://github.com/gurpreet0022/nlp_exploration

This repository explores various Natural Language Processing (NLP) techniques using the NLTK library in Python. It demonstrates these techniques on a sample dataset and performs sentiment analysis on movie reviews.
https://github.com/gurpreet0022/nlp_exploration

beginner-friendly nlp nlp-machine-learning nltk scikit-learn

Last synced: 21 days ago
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This repository explores various Natural Language Processing (NLP) techniques using the NLTK library in Python. It demonstrates these techniques on a sample dataset and performs sentiment analysis on movie reviews.

• Host: GitHub
• URL: https://github.com/gurpreet0022/nlp_exploration
• Owner: Gurpreet0022
• License: mit
• Created: 2024-12-22T09:46:01.000Z (25 days ago)
• Default Branch: main
• Last Pushed: 2024-12-22T09:50:24.000Z (25 days ago)
• Last Synced: 2024-12-22T10:30:19.168Z (25 days ago)
• Topics: beginner-friendly, nlp, nlp-machine-learning, nltk, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# NLP Techniques and Sentiment Analysis with NLTK

This notebook explores various Natural Language Processing (NLP) techniques using the NLTK library in Python. It demonstrates these techniques on a sample dataset and performs sentiment analysis on movie reviews.

## Tasks Performed

### NLP Techniques

1. **Data Loading and Preprocessing:** Loads a sample dataset for demonstrating NLP techniques.

2. **Tokenization:** Splits text into individual words.

3. **Stop Word Removal:** Removes common words that don't contribute to analysis.

4. **Stemming:** Reduces words to their base form.

5. **Part-of-Speech Tagging:** Assigns grammatical tags to words.

6. **Named Entity Recognition (NER):** Identifies named entities in the text.

7. **Lemmatization:** Similar to stemming, but finds the dictionary form of words.

8. **Corpora Exploration:** Accesses and explores text collections from NLTK's corpora.

9. **WordNet Exploration:** Analyzes word relationships using WordNet.

### Sentiment Analysis

1. **Movie Reviews Dataset:** Uses the NLTK movie reviews dataset for sentiment analysis.

2. **Feature Extraction:** Extracts relevant features (words) from the reviews.

3. **Naive Bayes Classifier:** Trains a Naive Bayes classifier to predict sentiment (positive/negative).

4. **Accuracy Evaluation:** Evaluates the classifier's accuracy on a test set.

5. **Saving the Classifier:** Saves the trained classifier using Pickle for later use.

## Libraries Used

- NLTK

- Pandas

- NumPy

- Pickle

## Datasets

- A sample dataset for demonstrating NLP techniques.

- The NLTK movie reviews dataset for sentiment analysis.

## Usage

1. Make sure you have the required libraries installed.

2. Upload the sample dataset to your Google Colab environment (if needed).

3. Run the notebook cells sequentially.