Machine learning with backpropagation What makes the neural network powerful is its capacity to learn based on input.

In machine learning, backpropagation is a widely used algorithm for training feedforward artificial neural networks or other parameterized networks with differentiable nodes.

All the frameworks used for Deep Learning automatically implement Backpropagation for CNN. But as we humans are curious, we want to know how it works and not let it be implemented automatically.

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world. Machine-learning algorithms are responsible for the vast majority of the artificial intelligence ...

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI. Every time a human or machine learns how ...

Machine learning is one of those buzz words that gets thrown around as a synonym for AI (Artificial Intelligence). But this really is not accurate. Note that machine learning is a subset of AI ...

Our latest Methods 101 video explains the basics of machine learning and how it allows our researchers to analyze data on a large scale.

The findings pave the way toward developing optically driven and energy-efficient machine learning technologies that reduce both the carbon footprint and costs of AI computation.

Machine learning isn’t just something locked up in an academic lab though. Lots of machine learning algorithms are open-source and widely available.

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...