GATE data science & AI important questions 2026

GATE Data Science & Artificial Intelligence (DA) Important Questions: GATE Data Science & Artificial Intelligence (DA) ...
Scientific Research Publishing

Maulud, D., & Abdulazeez, A. M. (2020). A Review on Linear Regression Comprehensive in Machine Learning. Journal of Applied Science and Technology Trends, 1, 140-147.

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
Scientific Research Publishing

Hope, T. M. H. (2020). Linear Regression. In A. Mechelli, & S. Vieira (Eds.), Machine Learning (pp. 67-81). Elsevier.

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
The New York Times

She Writes to Keep Her Sister Alive

“A Truce That Is Not Peace,” the Canadian novelist Miriam Toews’s first nonfiction book since 2001, is a discursive reflection on her father’s and sister’s suicides, 10 years apart. Miriam Toews’s new ...
Frontiers

Survival prediction modelling in patients with acute ST-segment elevation myocardial infarction with LASSO regression and explainable machine learning

Background: Acute ST-segment elevation myocardial infarction (STEMI) is a cardiovascular emergency that is associated with a high risk of death. In this study, we developed explainable machine ...
Hosted on MSN

Linear Regression Cost Function | Machine Learning | Explained Simply

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...
IEEE

Systematic Bias of Machine Learning Regression Models and Correction

Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large-valued ...