Machine learning (ML) expert Ted Dunning breaks down deep learning vs. "cheap learning" and lays out best practices for business success.

A concrete example of this is the difference between so-called "generative" and "discriminative" models. ... so I tend to go for super-simple machine learning algorithms like Naive Bayes.

For example, in solar cells, ... But a new paper in npj Computational Materials shows that even a simple machine learning model, trained with a modest amount of data, ...

“It is machine learning,” he continues. “It’s cheesy and cheap machine learning. It is cheap learning, not deep learning. But it’s incredibly valuable on a moment to moment basis, when you have 500 ...

For example, consider a dataset of x-ray scans used to train a machine learning model for cancer detection. Your data is imbalanced, with 90 percent of the training examples flagged as benign and ...

The takeaway is simple: Machine learning isn’t just about working smarter—it’s about making fintech better for everyone. It helps businesses grow while creating more meaningful connections ...

Machine learning is a powerful tool for the modern enterprise. It offers insights that extend far beyond business intelligence and data analytics. Written by eWEEK content and product ...

“That’s why quantum machine learning may be a good near-term application.” Quantum machine learning tolerates more noise than other kinds of algorithms because tasks such as classification, a staple ...

The creative new approach could lead to more energy-efficient machine-learning hardware. On a table in his lab at the University of Pennsylvania, physicist Sam Dillavou has connected an array of ...

This example uses a simple machine learning algorithm, which requires just a few model parameters. A more complex algorithm, such as for a deep neural network, ...