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 ...

In this special guest feature, Scott Clark, Co-founder and CEO of SigOpt, discusses why measurement should be the first step of any deep learning strategy. Before SigOpt, Scott led academic research ...

A research team investigated the efficacy of AlexNet, an advanced Convolutional Neural Network (CNN) variant, for automatic crop classification using high-resolution aerial imagery from UAVs. Their ...

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...