This project develops sentiment classification models for IMDB reviews using shallow RNN, unidirectional LSTM, and bidirectional LSTM. It employs GloVe embeddings, evaluates performance with accuracy, precision, recall, and F1 score, and aims to assess the impact of LSTM layers on model effectiveness.

Retrieve semantically similar Steam games.

Sentiment analysis on the IMDB dataset using Bag of Words models (Unigram, Bigram, Trigram, Bigram with TF-IDF) and Sequence to Sequence models (one-hot vectors, word embeddings, pretrained embeddings like GloVe, and transformers with positional embeddings).

Sentimental Analysis

Predict emotions (happiness, anger, sadness) from WhatsApp chat data using machine learning and deep learning models. Includes text normalization, vectorization (TF-IDF, BoW, Word2Vec, GloVe), and model evaluation.

Question answering using word embedding models (Word2vec , fastText , Glove)

Data and code for the machine learning exam assignment of MA Digital Text Analysis (2023).

Project building ML & DL models to detect spam messages.

Custom deep learning architectures for Sentiment Analysis and Image Classfication

Power of GloVe word embeddings in Android

Transfer Learning models in PyTorch

Vectorization Techniques in Natural Language Processing Tutorial for Deep Learning Researchers

This repository houses my assignments completed during the Deep Learning course as part of my Master's in Data Analytics program. Explore diverse projects showcasing hands-on applications of advanced neural networks and machine learning techniques.

Polarity prediction of tweets in Mexican Spanish using RNNs and word embeddings in PyTorch

This was a group project that i worked on for Data & Visual Analytics coursework at Georgia Tech. The motivation behind the project is to use ML, NLP to help job seekers with insights.

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

Generate captions for images, describing it

LSTM models for Sentiment Analysis