MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

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 ...

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

Learn how to implement linear regression from scratch in C++. A beginner-friendly guide to machine learning basics.

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...

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 ...

Objective: To develop an auxiliary diagnostic tool for schizophrenia based on multiple test variables using different machine learning algorithms. Results: Arg, TP, ALP, HDL, UA, and LDL were ...

Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...