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deep-neural-network

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.

Here are 159 public repositories matching this topic...

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

  • Updated Jul 3, 2024
  • Python
Splitter
WB_color_augmenter

WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab].

  • Updated Sep 20, 2024
  • MATLAB

Reinforcement learning (RL) implementation of imperfect information game Mahjong using markov decision processes to predict future game states

  • Updated Aug 24, 2022
  • JavaScript
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