BNLP is a natural language processing toolkit for Bengali Language.

a robust AI library for detecting profanity in russian language (regex/SVM based), библиотека для детекции нецензурных слов в русском языке

Transform AI-generated text into formal, human-like, and academic writing with ease, avoids AI detector!

Principles Of AI Lab Exercises

This project is a Python-based web scraper and data analyzer that extracts quotes, authors, and associated tags from the website Quotes to Scrape. It processes the data to create structured CSV files and includes functionalities for filtering and analyzing quotes by tags.

The Duolingo for certifications instead of languages!

Amazon Product Reviews: Sentiment Analysis with NLP

Know-Genius an AI Chatbot who's a General Knowledge Genius!

This repository implements a Next Word Prediction model using BiLSTM in PyTorch. It is trained on a dataset of Medium article titles and predicts the next word based on context. The project includes data preprocessing, model training, and Prediction.

An innovative system for filtering and categorizing movie reviews

Machine learning model for classifying news articles based on their headlines.

👨‍💻👨‍💻 Movie Recommendation system , this model is projecting five similar movies to user according to user input.

🤖 Automation Bot which can do textual extraction from a URL and perform text analysis and store into a file.

Text Classification for Resumes: Conducted Exploratory Data Analysis (EDA) on a vast collection of resumes. Organized the data using Bag of Words (BoW) and TF-IDF techniques. Built and evaluated multiple models, with Logistic Regression delivering standout performance. Created Word Clouds and Histograms.

Text Processing RNN leverages RNN and LSTM models for advanced text processing. It features deep learning techniques for NLP tasks, utilizing GloVe for word embeddings, aimed at both educational and practical applications.

A supervised deep learning project using Natural Language Processing(NLP) that classifies a given SMS as a spam/ham message.

The objective of this assignment is to extract textual data articles from the given URL and perform text analysis to compute variables that are explained

Sentiment analysis of tweets using TextBlob for labeling and RandomForest for classification.