Layers Outputs and Gradients in Keras. Made easy.
machine-learning
deep-learning
keras
mnist
keras-tutorials
keras-neural-networks
keras-visualization
visualize-activations
multi-inputs
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Updated
Aug 14, 2024 - Python
Layers Outputs and Gradients in Keras. Made easy.
The goal of this project is to build a neural network that takes an MNIST handwritten digit (0-9) image and a random number (digit 0-9) as inputs and returns the predicted class label (0-9) for the input image and its addition (sum) with the input random number as summed output (range 0-18) label as outputs.
Authenticate multiple inputs easily using keyed BLAKE2b.
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