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Natural Language Processing (NLP) Notebooks

Overview

This repository contains notebooks developed for the Natural Language Processing (NLP) course. Each notebook corresponds to key topics covered in the curriculum, providing practical insights and hands-on experience in the field of NLP.

Course Topics

The following topics are included in the course:

  • Text Preprocessing Techniques

    • Methods for cleaning and preparing text data for analysis.
  • Tokenization and Text Representation

    • Techniques for breaking down text into tokens and representing text data using various models.
  • N-grams and Language Models

    • Understanding n-grams and their application in building language models.
  • Part-of-Speech Tagging

    • Techniques for identifying and labeling parts of speech in sentences.
  • Named Entity Recognition

    • Methods for detecting and classifying named entities in text.
  • Sentiment Analysis

    • Approaches for analyzing sentiment and emotions in text data.
  • Word Embeddings and Representation Learning

    • Understanding word embeddings
  • Transformers and Attention Mechanism

    • Exploration of transformer architecture and attention mechanisms in NLP tasks.

Getting Started

To get started with the notebooks, clone this repository to your local machine:

git clone <repository-url>

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