Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles are available in the industry? Will I need to be a good ...

This important study employs a closed-loop, theta-phase-specific optogenetic manipulation of medial septal parvalbumin-expressing neurons in rats and reports that disrupting theta-timescale ...

The mean, variance, and autocorrelation of glucose dynamics are independently associated with coronary plaque vulnerability.

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

Background Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for ...

Abstract: The purpose of this work is to improve the detection of fraud websites using Novel Linear Regression Algorithm and Recurrent Neural Network Algorithm. Materials and Methods: Novel Linear ...

This is a machine learning-based web application built with Flask that predicts the estimated salary of an individual based on their: Years of Experience Education Level Location Previous Salary The ...

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...