Use Deep Learning model to diagnose 14 pathologies on Chest X-Ray and use GradCAM Model Interpretation Method

Deep Neural network using CNN pre-trained model to visually diagnose between 3 types of skin lesions

Evaluation of supervised predictions for two-class and multi-class classifiers

Machine-learning models to predict whether customers respond to a marketing campaign

Toolkit for Doing Research with ECMAScript-based Statistics (DRESS Kit)

Survival modelling using Cox proportional hazard regression model

The classification goal is to predict whether the client will subscribe (1/0) to a term deposit (variable y).

pyWitness performs data analyses and model fitting of recognition memory data, specifically eyewitness identification data.

Resample precision-recall curves correctly!

[Master Thesis 2017] Scripts for calculating metrics to assess performance of a drug design software.

Python code to obtain metrics like receiver operating characteristics (ROC) curve and area under the curve (AUC) from scratch without using in-built functions.

These codes are written as a part of ECE219 Large Scale Data Mining course at UCLA.

This project aims to predict the occurrence of diabetes using machine learning techniques. The dataset used for this analysis is the "diabetes_prediction_dataset.csv" file, which contains various features related to an individual's health condition.

Two-Dimensional Data Whitening and Receiver Operational Characteristic Determination

The repository contains the code for the various machine learning algorithms used to make a predictive analysis of tweets on GST in India

Explore how certain hyperparameters and features in a logistic regression model affect image classification

Human Resources Analytics

Wolfram Language (aka Mathematica) paclet for Receiver Operation Characteristic (ROC) functions.

Classification-Techniques-For-Fraud-Detection