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NLP - Natural Language Processing with Python

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Welcome to the Natural Language Processing (NLP) project repository! This project is dedicated to various Natural Language Processing tasks using Python.

Overview

Natural Language Processing involves the application of machine learning and deep learning techniques to understand and process human language. This repository serves as a comprehensive resource for various NLP tasks implemented in Python.

Key Features

  • Text Classification: Implementing classifiers for various text categories.
  • Named Entity Recognition (NER): Identifying and classifying named entities in text.
  • Sentiment Analysis: Determining the sentiment of textual content.
  • Language Translation: Building models for language translation tasks.
  • Speech Recognition: Processing and recognizing spoken language.

Projects

Project Name Description Kaggle GitHub
Sentiment Analysis: Predicting Product Recommendations via Text Analysis This project focuses on sentiment analysis to predict product recommendations through advanced text analysis techniques. Explore various machine learning algorithms and deep learning models for accurate predictions. Kaggle GitHub
Sentiment Analysis on Movie Reviews This project explores various pre-trained models for sentiment analysis on movie reviews. By leveraging Kaggle's TPU, I trained BERT, RoBERTa, DistilBERT, XLNet, GPT, BART, MobileBERT, ALBERT, and ELECTRA models, each for a maximum of 2 epochs to prevent overfitting. Kaggle Notebook 1 Kaggle Notebook 2 GitHub

Libraries and Tools

Key libraries and frameworks used in this project:

Getting Started

  1. Clone the repository:
    git clone https://github.com/huseyincenik/nlp_natural_language_processing.git