Machine Learning

From agriculture to banking, artificial intelligence is integral. These seven reasons are why machine learning affects everyday life.

Active learning has been around for a while in human education, but what is active learning in machine learning? Discover how this concept can improve AI.

Neural networks and deep learning are terms used interchangeably, but they aren’t the same thing. How do these two come together?

Machine learning is one of the most influential technologies of the current time, so the tools that let people build and manage these algorithms are essential. Take a closer look at the top machine learning tools available in 2023.

While natural language generation may not be the most recognizable term in AI, it powers some of the most common AI applications.

Applications for machine learning in healthcare are on the rise as doctors search for new ways to treat patients and save lives. But is machine learning really a remedy or a risk in the field of medicine?

Machine learning algorithms power the world’s AI models. Learn more about how these key algorithms work.

Hyper-automation is a relatively new concept that optimizes entire processes. Check out how it has helped companies and the considerations for applying it.

Machine learning programs won’t be a replacement for human ingenuity or creation, but they will give us a few tools to help shape the future. What language do these programs use?

How do machine learning researchers use graph neural network models? Check out these real-life examples of what’s possible.

Both PyTorch and TensorFlow, the two most popular deep learning frameworks, have their advantages, especially for those new to machine learning. This post breaks down the key differences between the two libraries.