Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Developing a decision tree project can feel a lot like logging into your Netflix or Hulu account. There are so many programming choices that you can stay glued to your laptop for a long, long time.

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 ...

Dr. James McCaffrey of Microsoft Research says the technique is easy to tune, works well with small datasets and produces highly interpretable predictions, but there are also trade-off cons. The goal ...