This is my final year project "customer reviews classification and analysis system using data mining and nlp". It analyzes and then classifies the customer reviews on the basis of their fakeness, sentiments, contexts and topics discussed. The reviews are taken from various e-commerce platforms like daraz and amazon.

Leveraging BERT and c-TF-IDF to create easily interpretable topics.

This collection features a series of NLP projects, covering diverse aspects. Explore projects in text processing, sentiment analysis, entity resolution, and more.

The primary goal of this project is to cluster the COVID-19 dataset into meaningful topics using advanced NLP techniques. By implementing the methods outlined in the article "BERT and clustering integrated modeling topic improved framework," we aim to uncover significant relationships between the variables in the dataset.

Topic Modelling for Humans

A diploma project focused on vectorizing scientific texts using the Top2Vec algorithm, with the aim of analyzing thematic groups, identifying trends, and visualizing the dynamics of interest in various topics in the field of computer science.

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

This project aims to provide developers and researchers with a powerful tool for working with text data, including tasks such as text summarization, topic modeling, named entity recognition (NER), translation, and speech-to-text conversion.

Interact, analyze and structure massive text, image, embedding, audio and video datasets

We use NLP techniques like sentiment analysis and topic modelling to analyze large volumes of customer reviews and extract valuable insights that can aid businesses in decision making

In my code portfolio, I generally try new techniques and methods in machine learning. I don't like only copying and pasting.

My Deep Learning Projects (Classification, Segmentation, Object Detection, NLP, Deep Multiple Instance Learning)

A Fast, Adaptive, Stable, and Transferable Topic Model

Automatic Gap-Fill Question Generation

Graph-based temporal topic modeling for very small corpora

Using text analytics to understand cultural patterns in philosophical texts. Exploring gender, author, region, and time-period differences, and extracting key philosophical concepts.

A Topic Modeling System Toolkit

Topic modelling para recomendación de libros, haciendo uso de Latent Dirichlet Allocation.

Code for On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling (AAAI 2024)

Research Project: Analysis of Chinese Financial Discourse Based on Topic Clustering and Emotional Evolution | Fall 2023 - Spring 2024