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

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 ...

Ernie Smith is a former contributor to BizTech, an old-school blogger who specializes in side projects, and a tech history nut who researches vintage operating systems for fun. In data analysis, it is ...

Learning how to predict future events from patterns of past events is a critical challenge in the field of artificial intelligence. As machine learning pioneer Yann LeCun writes, “prediction is the ...