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GitHub / crosstherubicon / Backprop_Hyper-parameters
Understanding hyperparameters of neural network architectures using 3 cost functions, 3 activation functions, 2 regularizations and dropout.
Stars: 1
Forks: 1
Open Issues: 0
License: None
Language: Jupyter Notebook
Repo Size: 1.63 MB
Dependencies:
0
Created: about 4 years ago
Updated: 11 months ago
Last pushed: over 3 years ago
Last synced: 11 months ago
Topics: activation-functions, backpropagation, brackprop-hyperparameters, cost-function, deep-learning, deep-learning-algorithms, dropout, dropout-keras, hyperparameters, irish-data, neural-network, neural-networks, regularization
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