Popular GitHub Repositories for Nltk

NLTK Source

Creating a software for automatic monitoring in online proctoring

The hands-on NLTK tutorial for NLP in Python

RSS feed aggregator with collections and NLP article summarization

NLP Cheat Sheet, Python, spacy, LexNPL, NLTK, tokenization, stemming, sentence detection, named entity recognition

:video_camera: A tool for automatic video creation and uploading on YouTube

? GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.

This repository consists of all my NLP Projects

This is a AI Based Smart Exam Proctoring System using python flask, mysql as database, yolov4

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

This repository provides everything to get started with Python for Text Mining / Natural Language Processing (NLP)

Sentiment Analysis of news on stock prices

Multi-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).

Bypass Ai detection using undetectable.ai

Text Summarization for Research Papers

Natural Language Processing notes and implementations.

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

Named entity extraction from Portuguese web text

Summarise YouTube videos and save time!

Java port of Python NLTK Vader Sentiment Analyzer. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.