https://github.com/devandrepascoa/nn_scratch
https://github.com/devandrepascoa/nn_scratch
Last synced: 10 months ago
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- Host: GitHub
- URL: https://github.com/devandrepascoa/nn_scratch
- Owner: devandrepascoa
- Created: 2020-04-22T02:45:40.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2023-11-17T14:40:14.000Z (over 2 years ago)
- Last Synced: 2023-11-17T15:58:36.588Z (over 2 years ago)
- Language: Python
- Size: 15.7 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# NN_Scratch
Neural network from scratch, implemented with numpy and a lot of patience with calculus and linear algebra, (vectorization and calculating proper gradients), recently implemented Gradient checking and Dropout regularization, now focusing on implementing a proper library, which I will be able to use to further understand the fundamental concepts of machine learning,
Performance of a [784,128,128,10] network for MNIST classification with 0.5 learning rate is at
97% for validation accuracy and 96% for training data accuracy(which means regularization has been properly implemented as it has generalized)
The start of the program execution
```
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( ` _) ( -~( -_ `, } BIG BRAIN MACHINE BY ANDRÉ PÁSCOA
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`~ -^( __;-,((()))
~~~~ {_ -_(())
`\ }
{ }
Starting training, NN dimensions: [784, 128, 128, 10]
Epoch:0,Cost:2.851550957041901, Accuracy:10.383333333333333
Validation Cost:2.2301635069375916, Validation Accuracy:19.29
Epoch:100,Cost:0.4705938394307374, Accuracy:86.16
Validation Cost:0.263984076214809, Validation Accuracy:92.39
Epoch:200,Cost:0.3546978889384424, Accuracy:89.82833333333333
Validation Cost:0.1997824425174201, Validation Accuracy:94.02000000000001
Epoch:300,Cost:0.2995063853680104, Accuracy:91.39333333333333
Validation Cost:0.16883666002554917, Validation Accuracy:95.05
Epoch:400,Cost:0.2639805195222709, Accuracy:92.41333333333334
Validation Cost:0.14901901587825286, Validation Accuracy:95.69
```