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

Overfitting in ML is when a model learns training data too well, failing on new data. Investors should avoid overfitting as it mirrors risks of betting on past stock performances. Techniques like ...