Information about Test

  1. Deep learning

    Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on artificial

  2. Deeper learning

    In U.S. education, deeper learning is a set of student educational outcomes including acquisition of robust core academic content, higher-order thinking

  3. Comparison of deep-learning software

    compares notable software frameworks, libraries and computer programs for deep learning. Licenses here are a summary, and are not taken to be complete statements

  4. Deep reinforcement learning

    Deep reinforcement learning (DRL) uses deep learning and reinforcement learning principles in order to create efficient algorithms that can be applied

  5. Q-learning

    Q-learning algorithm. In 2014 Google DeepMind patented an application of Q-learning to deep learning, titled "deep reinforcement learning" or "deep Q-learning"

  6. Artificial neural network

    particularly in image and visual recognition problems, which became known as "deep learning".[citation needed] Ciresan and colleagues (2010) showed that despite

  7. Machine learning

    hearing. Some successful applications of deep learning are computer vision and speech recognition. Decision tree learning uses a decision tree as a predictive

  8. Deepfake

    Deepfakes (a portmanteau of "deep learning" and "fake") are media that take a person in an existing image or video and replace them with someone else's

  9. Deep belief network

    In machine learning, a deep belief network (DBN) is a generative graphical model, or alternatively a class of deep neural network, composed of multiple

  10. Reinforcement learning

    reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. It differs from supervised