This project aims to clarify the role of meta data in music genre classification and how helpful or hurtful it can be to music recommendation systems. Much experimentation was done with multiple different machine learning models and results were analysed and collated into a single academic paper

"DressMeUp" project utilizes fashion images and color combinations to achieve image classification for clothing combinations. Algorithms include SGD (SVM), Passive Aggressive Classifier, ResNet50 CNN, and EfficientNetV2-S CNN with K-Means for color analysis. Achieved accuracy exceeds 90%. Built with Python, Scikit-Learn, TensorFlow, and Streamlit.

The Titanic dataset includes passenger information such as survival status, ticket class, gender, age, family relations aboard, fare, cabin, and port of embarkation. It's widely used for predictive modeling to understand survival patterns based on passenger attributes.

This project detects AI-generated text using an ensemble of classifiers: Multinomial Naive Bayes, Logistic Regression, LightGBM, and CatBoost. It includes robust data preprocessing, model development, and evaluation, ensuring accurate identification of AI-generated content from a diverse text dataset.

A simple sentiment analysis using SGD and LinearSVC for Amazon Reviews

Sharing both theoretical and programing ideas, that I came across at Introduction to Machine Learning course. notes, homework solution and python assignment

Consumer Complaint Classification using SGD Classifier

A basic NLP project on musical instruments reviews on Amazon.

This project was completed as part of the Applied Machine Learning course at Drexel University, Philadelphia. The project aimed to apply machine learning algorithms to analyze a dataset of consumer complaints and categorize them into different groups based on the issues related to goods or services.

Logistic regression and stochastic gradient descent approaches used to predict a binomial variable

Built various machine learning models for banks to develop effective credit rating

We built a model for Film Junky Union to detect negative reviews.

Tag Prediction Model for the Doubt Asking Platform. Suggests tags based on the user input question and question description.

The Mid-term 'Natural Language Processing' project by Duc Tran Van, Minh Nguyen Tan, Trung Nguyen Hoang

This repository has the implementation of Logistic Regression algorithm from scratch, using SGD (Stochastic Gradient Descent). Scikit Learn library is not used.

Multiclass classification of Youtube videos using text mining.

SGD classifier for the MINST dataset built using Eigen in C++

In this challenge, I build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).

Predicting client’s loan repayment abilities