Objective This study aimed to evaluate the prevalence and predictors of cardiovascular disease (CVD), chronic kidney disease ...
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Neural network cost functions: Which to use and why?
In this video, we will see what is Cost Function, what are the different types of Cost Function in Neural Network, and which ...
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Supervised learning made easy: Real-world example explained
In this video, we will study Supervised Learning with Examples. We will also look at types of Supervised Learning and its ...
Background The likelihood of HIV acquisition is increased following forced vaginal sex. This relates in part to ...
Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
Abstract: The recent development of advanced data analytics and machine learning promoted the introduction of diverse learning techniques designed to alleviate challenges related to two major ...
ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...
Abstract: Tabular data is the most prevalent form of structured data, necessitating robust models for classification and regression tasks. Traditional models like eXtreme Gradient Boosting (XGBoost) ...
The output variable must be either continuous nature or real value. The output variable has to be a discrete value. The regression algorithm’s task is mapping input value (x) with continuous output ...
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