Learn what overfitting is, why it happens, and how to prevent it in deep learning using techniques such as data augmentation, regularization, early stopping, and batch normalization.

Learn some tips to prevent overfitting and underfitting in deep learning, such as using appropriate data, regularization, cross-validation, and more.

In addition, deep learning is considered as black box and hard to interpret. These factors make deep learning not widely used in microbiome-wide association studies. In this work, we construct a ...

Training a Deep Learning model means that you have to balance between finding a model that works, i.e. that has predictive power, and one that works in many cases, i.e. a model that can generalize ...

Rebooting AI: Deep learning, meet knowledge graphs Knowledge graphs, the 20-year old hype, may have something to offer there. Written by George Anadiotis, Contributor Nov. 20, 2020 at 7:49 a.m. PT ...

Deep learning has been widely used in search engines, data mining, machine learning, natural language processing, multimedia learning, voice recognition, recommendation system, and other related ...