Deep learning requires ample data and training time. But while application development has been slow, recent successes in search, advertising, and speech recognition have many companies clamoring ...

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Nuix Ltd. (ASX: NXL), a global leader in data processing, investigative analytics and intelligent software, has today announced it has been granted a patent for pioneering a novel technology ...

Specialization: Machine Learning Instructor: Geena Kim, Assistant Teaching Professor Prior knowledge needed: Calculus, Linear algebra, Python Learning Outcomes Explain what multilayer perceptrons, ...

Deep learning pioneers Deep Yoshua Bengio, Geoffrey Hinton, and Yann LeCun outlines future directions for research in ACM paper.

This guide provides a simple definition for deep learning that helps differentiate it from machine learning and AI along with eight practical examples of how deep learning is used today.

Training these deep-learning networks can take a very long time, requiring vast amounts of data to be ingested and iterated as the system gradually refines its model to achieve the best outcome.

Early Bird uses 10 times less energy to train deep neural networks Novel training method could shrink carbon footprint for greener deep learning Date: May 18, 2020 Source: Rice University Summary ...