Overview: Free YouTube channels provide structured playlists covering AI, ML, and analytics fundamentals.Practical coding demonstrations help build real-world d ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...

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 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

We will build a Regression Language Model (RLM), a model that predicts continuous numerical values directly from text sequences in this coding implementation. Instead of classifying or generating text ...

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

The analysis of covariance (Ancova) is a widely used statistical technique for the comparison of groups with respect to a quantitative dependent variable in such a way that the comparison takes into ...

ABSTRACT: This paper proposes a universal framework for constructing bivariate stochastic processes, going beyond the limitations of copulas and offering a potentially simpler alternative. The ...

The Cox model is used to assess the effect of a given covariate on time-to-event outcomes in terms of HRs. For example, in a randomized clinical trial comparing a novel treatment regimen versus a ...