imbalanced

2017 repository

LightGBM no-show predictor + AWS deployment (EC2 + Elastic Beanstalk)

Implementation of semi and self supervised learning on Imbalanced Dataset

Quick notebook to refer to different ways to handle imbalanced datasets.

Introduction to imbalanced classification, TensorFlow regression, and anomaly detection.

We use the widely available Kiva Dataset to predict if a Kiva Loan posting will get funded or not

This python code is an individual work and also my thesis work which contains a loss function with penalty to solve the problem of imbalanced classes and also the simple ANN to detect if a transaction is fraudulent or not in the case of credit card fraud. So with this algorithm, we can easily detect fraudulent transaction with a good precision .

Predicting vessel transshipment (discharge) amounts using XGBoost regression trees on a very small dataset.

Implementation of C4.5 + Binarization (OVO / OVA) with/without SMOTE preprocessing. This way, multi-class imbalanced problems can be addressed

Machine learning application for real-time fraud detection using Python, Streamlit and scikit-learn.

Basic POC to showcase how to sample data for an imbalanced ad-clicks predictive model.

Classification on an imbalanced dataset, evaluating several model-resampling method combinations with hyperparameter tuning.

Predicting credit card defaults (Classification)