A flexible sentiment analysis classifier package supporting multiple pre-trained models, customizable preprocessing, visualization tools, fine-tuning capabilities, and seamless integration with pandas DataFrames.

Twitter Sentiment Analysis

E-Commerce Comment Classification with Logistic Regression and LDA model

Sentiment analysis on emotions dataset

Aspect based sentiment analysis is the determination of sentiment orientation of different textual review or post based on the aspect terms associated with that review or post. After pre-processing the data, classification report is obtained for multiple ML and Neural Network Models on training data-set and the best among them is then used for c…

Sentiment detection model using many-to-one LSTMs on airline text reviews and generate contextually relevant text by training on "Alice's Adventures in Wonderland".

Classic NLP Viterbi model for sentiment prediction task implemented with MIRA and SWVM algorithms

This project analyzes app reviews using sentiment classification powered by DistilBERT. It employs machine learning and natural language processing (NLP) techniques to determine sentiment as positive, neutral, or negative. The analysis provides valuable insights into user feedback for app improvement.

Repository of my NLP projects

An end-to-end Machine Learning project for sentiment analysis of Flipkart product reviews using NLP and MLflow. The system classifies customer reviews as Positive or Negative through text preprocessing, TF-IDF vectorization, and Logistic Regression. MLflow is integrated for experiment tracking, parameter logging, model management, and evaluation. T