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License: MIT License
My attempt to implement a generic deep learning platform using Python
License: MIT License
CodeFactor found an issue: Starting a process with a partial executable path
It's currently on:
code\core\kaggle_notebook.py:13
Attempt to implement convolution logic using my question at stack exchange https://stats.stackexchange.com/questions/328817/vectorization-of-a-convolution-layer
it should be a transformation matrix M that is mainly zeros with some identity matricies in strategic positions to:
CodeFactor found an issue: Duplicate Code
It's currently on:
code\core\scrap_notes.py:186-205
code\core\scrap_notes.py:224-239
CodeFactor found an issue: Duplicate Code
It's currently on:
code\core\kaggle_notebook.py:73-87
code\core\scrap_notes.py:96-110
redesign colnvolutions based on the jupyter notebook loaded and make it return a 3D tensor instead of a 2D matrix
also define kernels and a pooling layer
CodeFactor found an issue: Duplicate Code
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code\core\kaggle_notebook.py:131-145
code\core\scrap_notes.py:145-157
code\core\scrap_notes.py:212-224
CodeFactor found an issue: Unnecessary "else" after "return"
It's currently on:
code\core\kaggle_notebook.py:54
Make output layer activation function impact how loss function is calculated
in case of softmax it behaves different than sigmoid
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