GitHub - UdaikaranSingh/Coding-Basic-BackPropagation-Using-Numpy: This is basically a coding Experiment to develop code for doing basic back propagation on a simple mutli-layer neural network only using basically Numpy matrix multiplications

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Name		Name	Last commit message	Last commit date
Latest commit History 97 Commits
__pycache__		__pycache__
.DS_Store		.DS_Store
.gitignore		.gitignore
ProblemC.py		ProblemC.py
ProblemD.py		ProblemD.py
ProblemE.py		ProblemE.py
ProblemF.py		ProblemF.py
checker.py		checker.py
data.zip		data.zip
gradientchecker.py		gradientchecker.py
mainFile.py		mainFile.py
neuralnet.py		neuralnet.py
partC.png		partC.png
partD_0.0001.png		partD_0.0001.png
partD_0.001.png		partD_0.001.png
partE_ReLU.png		partE_ReLU.png
partE_sigmoid.png		partE_sigmoid.png
partE_tanh.png		partE_tanh.png
partF_[784, 100, 10].png		partF_[784, 100, 10].png
partF_[784, 25, 10].png		partF_[784, 25, 10].png
partF_[784, 47, 47, 10].png		partF_[784, 47, 47, 10].png
validate_data.pkl		validate_data.pkl

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This is basically a coding Experiment to develop code for doing basic back propagation on a simple mutli-layer neural network only using basically Numpy matrix multiplications