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.

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.

Extractive summarizationof medical transcriptions

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

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…

Spam Classifier project for my end-of-semester project for Intro to AI class. We were a group of four people. I worked on all the Naive Bayes models.

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

Spam Detection – Cluster SMS messages to “Spam” and “Ham” (Kaggle Challenge)

Turkish News Category Classification Tutorial

Train data collection interface for TTW backend.

Twitter US Airline Sentiment

Large Scale benchmarking of state of the art text vectorizers

Grocery Dataset Classification with Deep Learning in Keras and Tensorflow.

Built MultinomialNB, Logistic Regression, Random Forests and LSTM with the TF-IDF vectorizer for fake and real news classification. Also performed K-means unsupervised algorithm with PCA and t-SNE.

We watch and read a lot of news daily. These news have a great impact on our lives and on the society as a whole. It can generate positive or negative impact on a person and can even shake the entire system of the country. So our model, thus, uses natural language processing and classifies the news headlines into positive, negative or neutral im…

Many countries speak Arabic; however, each country has its own dialect, the aim of this project is to build a model that predicts the dialect given the text.

The document classification solution should significantly reduce the manual human effort in the HRM. It should achieve a higher level of accuracy and automation with minimal human intervention.

NLP tutorials and guidelines to learn efficiently

Implementation of a search engine using a vector space model.