PyTorch is one of the most popular tools for building AI and deep learning models in 2026.The best PyTorch courses teach both ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine ...

Traditional lending relies on collateral and a financial history that productive smallholder farmers may find difficult to ...

To our knowledge, this analysis is the largest EHR-based study for identifying drug repurposing candidates for ALS. We identified several drugs that warrant further assessment as therapeutic options ...

Statsmodels helps analyze data using Python, especially for statistics, regression, and forecasting.The best Statsmodels ...

Objectives To evaluate whether type 2 diabetes mellitus (T2DM) presence and severity are associated with differences in ...

Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

Abstract: In the banking sector, predicting customer loan eligibility is a crucial task. This paper presents a study of using machine learning algorithms to predict loan eligibility of customers based ...