This repository includes exercises about Linear Regression and Logistic Regression. It follows a structured journey from simple linear models to more complex techniques including regularization and ...

In this article, we firstly give an unified interpretation for the relationship between two methods through the analysis of linear networks in the context of statistical regression; i.e. linear ...

Any home gardener knows they have to tailor their watering regime for different plants. Forgetting to water their flowerbed ...

Learn how to build your own GPT-style AI model with this step-by-step guide. Demystify large language models and unlock their ...

Machine learning interview questions now focus on both theory and real-world applications.Understanding basics like overfitting, bias, and regres ...

SEN. Loren Legarda honors the extraordinary men and women who serve as the very lifeline of the nation’s humanitarian and welfare response, calling for stronger institutional support, including ...

Most dynamical models introduced in the past were linear, which means that they assumed that changes in neural activity would follow a simple structure. While linear models tend to be easier to ...

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Diffusion models are a powerful class of techniques in ML for generating realistic data, but they are highly prone to overfitting, especially with limited training data. While data augmentation such ...

In the paper, author considers a new method for constructing the quasi-equilibrium thermodynamics of a system of ...

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