Welcome to my Text Summarization project! This project utilizes machine learning techniques to automatically generate concise summaries of given text inputs.

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis, NLP processing and ML, achieving the functionality of a Content based movie recommender system

Welcome to the Artificial Generative Intelligence Chatbot project! This innovative chatbot utilizes neural networks to provide intelligent responses hosted through flask server for better visualization

Developed web app using NLP & Django to summarizes the articles which are fetched from News API according to users' prefilled country preference. Deployed this model on Heroku platform.

Use web scraping and NLP to find the most frequent words in one of two pieces of classic literature: Herman Melville's novel, Moby Dick, or Peter Pan by J. M. Barrie.

My website.

The web app uses logistic regression on a dataset of 20,000 news articles, achieving 96% accuracy. It employs NLTK for text preprocessing and TF-IDF for feature extraction.

Application enabling to search through the General Comments/ Recommendations adopted by the UN Treaty Bodies (based on keywords, concerned groups and customized labels) and analyze search results.

A simple web app to classify the sentiment of a person conveyed through speech as positive, negative or neutral through a machine learning approach.

Explore our interactive chatbot for quick info on massages, powered by Flask and NLTK.

This system is totally based on providing text-based functionalities on a single platform. It is developed using NLTK, Python, Django, HTML, CSS, Bootstrap, OCR.

In this work we will study the construction of a system of answering questions, question answering systems have always been a major branch of AI and NLP

A short data analysis project of AirBnB listings in Berlin. Aspects of the analysis include data wrangling, exploratory analysis of the price, location, property, user reviews data and basic topic extraction using user reviews.

Research about NLP.

Using BeautifulSoup to analyze HTML and NLTK VADER to do sentiment analysis on news headlines

Effortlessly analyze text composition with our complimentary online tool. Seamlessly count words, sentences, characters, and paragraphs to gain valuable insights into your written content.

Exploratory text analytics project to examine cultural trends through analysis of 2016-2017 news articles.

Build a classifier to predict news authenticity