Tunable full text search engine in JavaScript that: (1) works natively on web apps like Express.js; (2) easy to customize (via BM25) to specific types of documents (e.g. tweets, scientifc journals); (3) is deployable on either the client-side or the server side.

NLP based Classification Model that predicts a person's personality type as one of the 16 Myers Briggs personality types. Extremely challenging project dealing with correlation between human psychology and casual writing styles and handling heavily imbalanced classes. Check the app here - https://mb-predictor-motetuzs5q-uc.a.run.app/

This repository contains the code for basic kind of E-commerce recommendation engine. By using the concept of TF-IDF and cosine similarity, we have built this recommendation engine.

Turkish News Category Classification Tutorial

Skincare recommendation android application that uses dataset from Kaggle and scrapped data from cosmetics websites to work a Tf-IDF vectorizer for content based filtering, and KNN and Decision trees for collaborative based filtering. The notebook also contains other approaches for POC including SVD. Backend APIs are based on Flask, Android appl…

A simple Django-based resume ranker website where recruiters post their jobs and candidates applies for their desired vacancies. The system gets the document similarity between the job description and the candidate resumes, generates similarity scores using the KNN model, and rank or shortlist the candidate resumes.

Extractive summarizationof medical transcriptions

NLP tutorials and guidelines to learn efficiently

Twitter Sentiment Analysis Using InSet (Indonesia Sentiment Lexicon) and Random Forest Classifier

Large Scale benchmarking of state of the art text vectorizers

Extract textual information from Amazon products reviews and draw correlations through regression and fluctuation analysis.

Text Classification for Sentiment Analysis using Female Daily's Reviews Dataset

Twitter Sentiment Analysis Using Vader Lexicon and Random Forest Classifier

Sistema de recomendación de películas basado en contenido. Utilizando TF-IDF y la similitud del coseno. La data fue extraída, transformada y analizada para el entrenamiento del modelo. Disponibilizandolo junto con la data limpia para futuras consultas, a través del despliegue con FastAPI y Render.

Scrapped tweets using twitter API (for keyword ‘Netflix’) on an AWS EC2 instance, ingested data into S3 via kinesis firehose. Used Spark ML on databricks to build a pipeline for sentiment classification model and Athena & QuickSight to build a dashboard

Course Project of Information Retrieval.

Compilation of Information Retrieval codes.

Implementation of a search engine using a vector space model.

Application of Machine Learning Techniques for Text Classification and Topic Modelling on CrisisLexT26 dataset.