The GeniSys NLU Engine includes a combination of a custom trained DNN (Deep Learning Neural Network) built using TFLearn for intent classification, and a custom trained MITIE model for entity classification.

A bespoke NLP Chatbot trained using a corpus of Reddit data.

Sentiment analysis on tweets analyzing any trade-able asset (Cryptocurrency) using Machine Learning and statistical classification model

This sentiment analysis API uses Flask-restful and provides a positive or negative sentiment response to input query.

Braggi is a Python based Contextual Chatbot Framework, which hopes to integrate all the necessities for a great chatbot framework, to satisfy both enterprise and general audiences alike. Development still underway, more features on the way 😄

A sentiment analysis and web-sockets application with twitter's streaming api

Sentiment analysis, analyzing user’s textual reviews, to perform a binary classification task (positive or negative mood). Designed a machine learning pipeline able to achieve an F1 score of 96.7% on unseen reviews.

This is an information retrieval engine running on the shoulders of ntlk library.

Not your normal social media market!

This repository contains two Python scripts for Natural Language Processing (NLP) tasks and text summarization, as well as a requirements.txt file specifying the necessary dependencies.

Exploratory Analysis of Amazon Product Reviews Dataset comprising of various categories spanning over 14 years

A movie recommender system that uses SBERT for embedding and cosine similarity for recommendations.

Are you feeling bored? Well never again because! Our little digital friend Sophie is here for you to talk. Ask her questions, tell her about yourself and she will listen and interact with you always.

Natural Language Processing pipeline including fundamentals, feature engineering and modeling.

In this repository, the project on NLP-based chatbot that generates responses based on the command given to the system.

In this study, I utilized the unsupervised approach Kmeans to cluster/group reviews in order to discover major topics/ideas within the sea of text. This applies to all textual evaluations. In this series, I've concentrated on Twitter data of Vodaphone, which is more real-world and sophisticated than evaluations acquired via survey or review forms.

Which beverage reigns superior? An analysis of the great Tea vs Coffee debate ☕️

OfficeBot is a simple conversational chat bot web app built on Flask and ChatterBot for answering questions regarding office hours.

The Text Summarizer Web Application utilizes Python, Flask, NLTK, and Bootstrap for creating concise summaries from long texts. No frills, just an efficient tool for simplifying complex content.

This project involves comprehensive data analysis and application development using a dataset of approximately 160K TV shows.