A fully connected linear neural network to recognize handwritten digits trained on the MNIST dataset
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Updated
Apr 28, 2020 - Jupyter Notebook
A fully connected linear neural network to recognize handwritten digits trained on the MNIST dataset
Fully Connected Forward Feed Neural Network
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This is the code for a fully connected neural network. The code is written from scratch using Numpy, without using any ready-made deep learning library. In this, classification is done on the MNIST dataset. It is generalized to include various options for activation functions, loss functions, types of regularization, and output activation types.
This repository contains a collection of fully connected benchmarks from VNNCOMP 2022-2024. It is designed to offer a more organized version of the existing benchmarks, making it easier to test new software. We recommend cloning the 'benchmarks_vnncomp' repository, which includes this repository as a submodule.
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