Wikidata embedding

NLP with NLTK for Sentiment analysis amazon Products Reviews

Implementation of a search engine using TF-IDF and Word Embedding-based vectorization techniques for efficient document retrieval

NLP Expedition

Amazon SageMaker Local Mode Examples

This project implements a semi-supervised approach to classify UN speeches. Utilized BERT, Gensim, Node2Vec and Tensorflow

Task-1 : Sentiment Analysis (Text Analysis+ Sentiment Analysis+ LDA model) Task-2: Random Forest Model for booking completion

This application is built for employers looking for candidates against a particular job description .

Machine Learning Practise

🦆 Contextually-keyed word vectors

Mayabati is a personal AI chef designed for enhancing culinary experience. Crafted by Biswadeb Mukherjee, a leading developer of ParseSphere Innovations.

A novel approach towards video-ranking using intent and relevance feedback

I performed sentiment analysis aimed at determining the sentiment of 50000 imDB movie reviews, whether they are positive, negative, or neutral. I employed various NLP approaches including lexicon based approaches, machine learning models, PLM models, and hybrid models, and assessed the performance on each type of model.

Code, données et documentations de l'atelier "Apprentissage automatique pour la classification textuelle" organisé dans le cadre de l'Action Nationale de Formation "Exploration documentaire et extraction d'information" CNRS-INRAE en 2020-21.

This repository contains code and resources for a SMS (Short Message Service) classification project using Word2Vec embeddings. The goal of the project is to classify SMS messages into spam or non-spam categories. The Word2Vec model is utilized for word embeddings, capturing semantic relationships between words in the SMS corpus.

A django web backend server that has single api for collecting sentiment text as json format, analyze them with a huggingface pretrained model and return the sentiment of the text as a json response.

A resume filtering based on natural language processing

NLP notebooks