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https://github.com/huseyincenik/nlp_natural_language_processing

NLP (Natural Language Processing)
https://github.com/huseyincenik/nlp_natural_language_processing

albert bart bert-model distilbert gpt gpt2 huggingface huggingface-transformers natural-language-processing nlp nlp-machine-learning nltk-library roberta roberta-model sentiment-analysis t5 xlnet

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NLP (Natural Language Processing)

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# NLP - Natural Language Processing with Python

![image](https://github.com/huseyincenik/nlp_natural_language_processing/assets/127469334/8ddb6700-e38b-4de9-a272-8cf6c8c4e4b8)

[Credit](https://www.google.com/url?sa=i&url=https%3A%2F%2Famazinum.com%2Finsights%2Fwhat-is-nlp-and-how-it-is-implemented-in-our-lives%2F&psig=AOvVaw2FXM9w7OuamLSzuE_O2kzy&ust=1702465524295000&source=images&cd=vfe&opi=89978449&ved=0CBIQjRxqFwoTCIDL57jgiYMDFQAAAAAdAAAAABAD)

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](https://www.kaggle.com/huseyincenik/sentiment-analysis-predicting-product-recommends) | [GitHub](https://github.com/huseyincenik/nlp_natural_language_processing/tree/main/sentiment_analysis_predicting_product_recommendations_via_text_analysis) |
| 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](https://www.kaggle.com/code/huseyincenik/transformers-for-sentiment-classification-1) [Kaggle Notebook 2](https://www.kaggle.com/code/huseyincenik/transformers-for-sentiment-classification-2) | [GitHub](https://github.com/huseyincenik/nlp_natural_language_processing/tree/main/projects/transformers_for_sentiment_classification) |
| Medical RAG QA App | A question-answering application for medical queries using Meditron 7B LLM, Qdrant Vector Database, and PubMedBERT Embedding Model. | - | [GitHub](https://github.com/huseyincenik/nlp_natural_language_processing/tree/main/projects/rag/medical_rag_qa_app) |

## Libraries and Tools
Key libraries and frameworks used in this project:
- [NLTK](https://www.nltk.org/)
- [spaCy](https://spacy.io/)
- [Transformers](https://huggingface.co/transformers/)
- [TextBlob](https://textblob.readthedocs.io/)
- [SpeechRecognition](https://pypi.org/project/SpeechRecognition/)

## Getting Started
1. Clone the repository:
```bash
git clone https://github.com/huseyincenik/nlp_natural_language_processing.git

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