Tune Artificial Neural Nets By Hand

Version 1.5.0 (6.57 KB) by Zachary Danziger
Educational tool for exploring neural network tuning both by hand and with backpropagation.
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Updated 14 Feb 2022

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This tool is designed to build intuitions for how ANNs work. The user can tune the weights of a classification ANN manually, by using UI sliders to update weight values, datasets, and activation functions. The results are displayed both as a classification landscape (like the neural network playground) and as a network diagram. The main feature is control over individual weights to help demonstrate the way ANNs compute classifications and why backpropagation is powerful, and what the limits of particular ANN architectures are.

Cite As

Zachary Danziger (2024). Tune Artificial Neural Nets By Hand (https://www.mathworks.com/matlabcentral/fileexchange/105365-tune-artificial-neural-nets-by-hand), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.5.0

Added new features (e.g., loading your own datasets and adjustability for the number of points displayed) and corrected a bug that made the network architecture slightly different than what the documentation described.
1.0.0