Predicting long-term and short-term Video Memorability using Semantic and Video features.

Joint work product with co-authors Chelsea Jin and Matthew Ye for at the virtual ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop held on Sept. 22-25, 2020. Data engineering support from Nick Barbour.

Classification model to predict if the client will subscribe to a term deposit based on the given bank dataset

Test and comparison of ensemble method with naive bayes classifier on 5 different data sets.

mlr3 extension package for ensemble machine learning

PREDICTIVE ANALYTICS

A light-weight Kaggle challenge to predict crabs' age

This project focuses on predicting the likelihood of diabetes in individuals using ensemble machine learning models. It combines various ensemble techniques, including Random Forest, AdaBoost, Gradient Boosting, Bagging, Extra Trees, XGBoost, Voting Classifier and some others to get predictions.

A series of notebook submissions I've done for the Kaggle Playground Series Competition.

This project has effectively analyzed house price trends and prediction using machine learning, emphasizing data cleaning, exploratory analysis, and regression modeling to gain insights into dataset patterns and structures.

Debt Insolvency Income Prediction using Data Science

Design of several classifiers to discriminate between calcification and masses, as well as, benign and malignant ones of mammography films.

Comparison of ensemble learning methods on diabetes disease classification with various datasets

Predicted the breast cancer in patient using Ensemble Techniques and evaluated the model

This notebook is for famous Kaggle competition Titanic.