Overall, my advice on deep learning is to look before you leap and watch for the changes, as they are happening quickly.

Deep learning, a subset of machine learning, refers to machine learning that takes place on artificial intelligence neural networks.

Key pros and cons of deep learning include its ability to handle large amounts of unstructured data and achieve high accuracy in challenging tasks, both of which are significant advantages.

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

Comparing AI models and human brains The similarity with human language doesn't stop here, however. Research published in Nature Neuroscience demonstrated that these artificial deep-learning ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly a… ...

Remember how deep learning figures out representations of the “language” of images? A deep learning model can learn what’s called a "latent space" representation of images.

OpenAI has just announced GPT-4, the latest iteration of its deep learning language model that is touted to be smarter and more capable than ChatGPT.