Assignments repository for Fall 2024 Multivariate Methods course

Using advanced control and computer vision techniques in an easy way for embedded

Implementation of algorithms such as normal equations, gradient descent, stochastic gradient descent, lasso regularization and ridge regularization from scratch and done linear as well as polynomial regression analysis. Implementation of several classification algorithms from scratch i.e. not used any standard libraries like sklearn or tensorflow.

Explore insightful projects on data analysis with MATLAB: k-means, k-medoid, and LDA. Polished PDF reports generated using LaTeX showcase valuable insights from diverse datasets. Discover the power of numerical methods in extracting knowledge from data!

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.

Analysis of the similarity between articles based on their content using TF-IDF and LDA

ML-algorithms from scratch using Python. Classic Machine Learning course.

High performance topic modeling for Ruby

A project analyzing user tweets about the 2023 BSI ransomware attack using clustering and topic extraction methods. Persona analysis is performed on both approaches, with a comparison of the results to extract key insights.

Pattern recognition involves classifying data into categories based on features, playing a vital role in applications like image and speech recognition. This project implements a system that enhances classification accuracy by utilizing Grey Wolf Optimization for feature selection and a Gaussian Naive Bayes classifier for efficient classification.

A revised version of Polo

'Coleridge Initiative - Show US the Data' Competition on kaggle

A versatile Python package engineered for seamless topic modeling, topic evaluation, and topic visualization. Ideal for text analysis, natural language processing (NLP), and research in the social sciences, STREAM simplifies the extraction, interpretation, and visualization of topics from large, complex datasets.

This repository contains code and resources for performing Natural Language Processing (NLP) analysis on budget speeches delivered by various finance ministers. The project leverages spaCy, Gensim, and Plotly to uncover insights from historical Indian budget speeches.

A simple LDA topic modeling sample

A simple LDA topic modeling sample.

Topic Modeling on “Coupang” App Reviews [Korean Text Processing]