30 lines
1.0 KiB
Markdown
30 lines
1.0 KiB
Markdown
# Shallow Neural Network Training Coursework
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Evaluating a neural network using the MatLab `cancer_dataset`. Development contained in the [nncw.ipynb](nncw.ipynb) notebook.
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1. Evaluate the network's tendency to overfit by varying the number of epochs and hidden layers being used
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2. Multiple classifier performance using majority vote
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3. Repeat 2 with two different optimisers (`trainlm`, `trainrp`)
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4. ***Extension***: Distinguish between two equi-probable classes of overlapping 2D Gaussians
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## Timing
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### exp 1
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CPU: 2min 36s ± 1.66 s per loop (mean ± std. dev. of 2 runs, 2 loops each)
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GPU: 3min 5s ± 2.95 s per loop (mean ± std. dev. of 2 runs, 2 loops each)
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### exp 2
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CPU: 26 s ± 62.9 ms per loop (mean ± std. dev. of 2 runs, 2 loops each)
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GPU: 57.6 s ± 46.7 ms per loop (mean ± std. dev. of 2 runs, 2 loops each)
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### exp 3
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CPU: 1min 19s ± 1.6 s per loop (mean ± std. dev. of 2 runs, 2 loops each)
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GPU: 3min 25s ± 280 ms per loop (mean ± std. dev. of 2 runs, 2 loops each) |