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.

Deep learning is a kind of machine learning just as cycling is a kind of exercise. Understanding deep learning is easier if you have a basic idea of what machine learning is all about.

The Education and Culture Office of East Kalimantan Province is enhancing the implementation of a deep learning approach at ...

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

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 ...

In the future, this approach could help to deepen the present understanding of deep learning algorithms and the processes through which they learn to reliably tackle specific tasks.

These advanced models use deep learning to analyze input sequences and predict likely outputs, making them indispensable tools for AI-driven text generation and contextual understanding.

By adapting techniques from the domain of artificial intelligence, such as deep learning, cognitive scientists from Osnabrück will study the core principles of human vision over the next five ...

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 ...