The repository contains code for fully connected neural network & also a demo.py file used to define & run the network. A decent variety of tests are implemented and can be seen in the solution.ipynb notebook(end). The network is designed to classify MNIST digit recognition dataset.
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./code folder:
- contains original files with implemented classes
- Added tests_all.py file which contains code used for creating plots & testing variations in the parameters
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report.pdf:
- Contains report for the network performance on different parameters
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Solution.ipynb contains the full standalone work :
- Fully implemented classes
- Demo run
- Testing code
- variation tests
- Report generation python code & markdown
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Solution.html is just the html version for this.
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I have added my results.pkl file, which is essentially the object where I have stored results from testing.