A comprehensive reference for all topics related to Natural Language Processing

Python library for feature selection for text features. It has filter method, genetic algorithm and TextFeatureSelectionEnsemble for improving text classification models. Helps improve your machine learning models

Using Spacy and NLTK module with Tf-Idf algorithm for text-summarisation. This code will give you the summary of inputted article. You can input text directly or from .txt file, .pdf file or from wikipedia url.

Document based ChatGPT

This is a Flask backend that allows users to upload a PDF file and receive a simplified and humorous explanation of its contents using OpenAI's GPT-3 API. The application uses NLTK to split the PDF text into smaller chunks to stay within the API's maximum token limit, and PyPDF2 to extract the text from the PDF file.

A prototype legal text search engine that uses a semantic search algorithm in order to find related keywords and sort the results by relevance.

a repo for everyday Natural Language Processing in Python

This repository contains code for generating blog content using the LLama 2 language model. It integrates with Streamlit for easy user interaction. Simply input your blog topic, desired word count, and writing style to generate engaging blog content.

A software designed to read messages to make it convenient for people to go through big messages and understand them easily in an efficient manner.

Natural Language Processing

This project provides a simple script for determining the sentiment of a text input using TextBlob library in Python. It also returns the most positive and most negative sentence in the input text. The script can be used as a standalone tool or integrated into other projects.

"Detect sarcasm effortlessly! This Python app uses NLP and ML to analyze text sentiment, distinguishing sarcastic tones. With a user-friendly interface, input any text for real-time sarcasm identification. Achieve accurate results through advanced sentiment analysis techniques and trained models."

Experience simple Text-to-Speech (TTS) functionality using pyttsx3 module, compatible with various speech engines like NSSpeechSynthesizer, SAPI5, and eSpeak.

training literature bert classification.