Transform AI-generated text into formal, human-like, and academic writing with ease, avoids AI detector!
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
Prompt Engineering using LangChain NoteBooks From Scratch
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!
Text Humanizer Pro is a Python-based project with a Streamlit frontend that transforms raw AI-generated text into natural, human-like writing.
Real-time crypto & stock news dashboard with sentiment analysis. Powered by CoinDesk, CoinTelegraph, Yahoo Finance RSS + VADER. Shows market mood, categories, and live updates in a sleek dark theme.
Amazon Product Reviews: Sentiment Analysis with NLP
An innovative system for filtering and categorizing movie reviews
Machine learning model for classifying news articles based on their headlines.
Nintendo Switch 2 Subreddit Text Analysis
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.
Python app that gives advice on which hospital department you should consult based on symptoms.
This project demonstrates basic Natural Language Processing (NLP) techniques using NLTK, including sentence tokenization, word tokenization, stopword removal, and stemming. It showcases how raw text can be transformed into a normalized format suitable for machine learning and text analytics tasks.
This project demonstrates a basic NLP text preprocessing pipeline using Python and NLTK, including sentence tokenization, word tokenization, stopword removal, and lemmatization for clean and structured text data.
NLP-based SMS spam detection using machine learning algorithms (Naive Bayes).
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