Deep learning for non sequential data regression

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Anas Rao
Anas Rao il 4 Ago 2022
Risposto: Meet il 25 Set 2024
Does deep learning is applicable for non sequential data for regression and if yes which models are preffereably applied for training purpose and any useful material/tutorial for learning prespective?

Risposte (1)

Meet
Meet il 25 Set 2024
Hi Anas,
Yes, deep learning can be applied to non-sequential data for regression tasks. MATLAB's Deep Learning Toolbox offers a variety of models and functions that can be effectively utilized for this purpose.
Here are some models you can consider for regression tasks:
  • Feedforward Neural Network: These are fundamental neural networks where connections between nodes do not form loops. They are particularly well-suited for handling regression tasks with non-sequential data.
  • Convolutional Neural Network: Although typically used for image data, these networks can also be adapted for regression tasks.
You can refer to the resources below for more information:
  1. https://www.mathworks.com/help/releases/R2019b/deeplearning/ref/feedforwardnet.html
  2. https://www.mathworks.com/help/releases/R2019b/deeplearning/ug/introduction-to-convolutional-neural-networks.html
  3. https://www.mathworks.com/help/releases/R2019b/deeplearning/examples/train-a-convolutional-neural-network-for-regression.html
Hope this helps!!

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