Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...

Specific problems have been studied simultaneously by different areas, using their own concepts and definitions. When each area defines a solution to this problem, it may result in similar, analogous, ...

This paper evaluates three approaches to address parameter proliferation issue in nowcasting: (i) variable selection using adjusted stepwise autoregressive integrated moving average with exogenous ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

Jake Fillery is an Evergreen Editor for Game Rant who has been writing lists, guides, and reviews since 2022. With thousands of engaging articles and guides, Jake loves conversations surrounding all ...

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...

1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...

Teachable Machine is an active way to help students learn about AI creatively. When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. Teachable Machine ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...