Our data science expert continues his exploration of neural network programming, explaining how regularization addresses the problem of model overfitting, caused by network overtraining. Neural ...

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...