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 ...

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 ...

In May 2025, TikTok was fined roughly $600 million under the General Data Protection Regulation (GDPR) for failing to prove EU user data was sufficiently protected. This penalty should be a wake-up ...

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 ...

Artificial Intelligence (AI) is changing how people trade cryptocurrencies. AI algorithms can process enormous amounts of data, recognize market trends, and generate crypto signals that alert buyers ...

Neural network dropout is a technique that can be used during training. It is designed to reduce the likelihood of model overfitting. You can think of a neural network as a complex math equation that ...