In 2006–2011, “deep learning” was popular, but “deep learning” mostly meant stacking unsupervised learning algorithms on top of each other in order to define complicated features for ...

8 practical examples of deep learning. Now that we’re in a time when machines can learn to solve complex problems without human intervention, what exactly are the problems they are tackling?

Algorithms and deep learning: the best of both worlds. Veličković was in many ways the person who kickstarted the algorithmic reasoning direction in DeepMind.

Then I’ll discuss 14 of the most commonly used machine learning and deep learning algorithms, and explain how those algorithms relate to the creation of models for prediction, classification ...

This is what separates neural networks and deep learning. A basic neural network probably has one or two hidden layers, ... Efficiency: When a deep learning algorithm is properly trained, ...

Deep learning is good at finding patterns in reams of data, but can't explain how they're connected. Turing Award winner Yoshua Bengio wants to change that.

Deploying deep learning algorithms on embedded platforms involves a structured process that optimizes models, considers hardware constraints, and addresses real-time performance requirements. By ...

Deep learning algorithms allow computers to learn from large amounts of data and are known for advancing the state of the art in the artificial intelligence field, leading to smarter cancer treatments ...