Do computer science curriculums need to spend more time explaining the weaknesses of today’s correlative deep learning rather than merely reinforcing its hype and hyperbole?

Deep learning models can be very complex and understanding their internals can be challenging. Users will trust these models more if they understand how the models are arriving at their decisions.

Learning about deep learning A machine capable of reacting to real-world visual, auditory or other type of data -- and then responding in an intelligent way -- has been the stuff of science ...

Why is the paper “Understanding Deep Learning Requires Rethinking Generalization” important? This question was originally answered on Quora by Eric Jang.

Jessica Yung talks about the foundational concepts about neural networks. She highlights key things to pay attention to: learning rates, how to initialize a network, how the networks are ...

Understanding the Pathologies of Deep-Learning AIs Engineering and clinical approaches will combine to improve the minds of AI. Posted October 12, 2019 ...

Facebook announced today that it can now do that with Deep Text, a deep learning-based text-understanding engine running a neural network that can understand with near-human accuracy the textual ...