Measure and visualize machine learning model performance without the usual boilerplate.

Machine learning utility functions and classes.

Script to compute Precision, Recall, AvP and MAP and to plot PR curves in the context of Information Retrieval evaluation.

This code build up a predicting model use the Machine learning algorithms such as Decision Tree, k-Nearest Neighbors etc. on the Vehicle to predict the departure action

A credit risk text classification pipeline designed to simulate real-world modeling workflows. This project uses financial text data to predict borrower risk, incorporating data cleaning, NLP preprocessing, and model evaluation—emphasizing skills in feature engineering, model pipeline structuring, and explainable machine learning.

Run histogram-based gradient boosted trees binary classifier on generated data and interpret results with standard metrics, SHAP, and supervised clustering

Light-weight package for classification metrics computed on streams or minibatches of data. Mainly for area under the curve (AUC) of precision-recall (PR) or receiver operating characteristic (ROC) curves. Supports multi-class setting with either macro- or micro aggregation..