Implementations of neural networks in python for the classification of MNIST datasets.
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Updated
Apr 6, 2024 - Jupyter Notebook
Implementations of neural networks in python for the classification of MNIST datasets.
Assignment 1 : To build a neural network using softmax as activation function
JavaFx Application for Convolutional Network to perfom Image Classification using Softmax Output Layer, Back Propagation, Gradient Descent, Partial Derivatives, Matrix Flattening, Matrix Unfolding, Concurrent Task, Performance Histogram, Confusion Matrix
The implementation of Coordinate Descent Method Accelerated by Universal Metaalgorithm with efficient amortised complexity of iteration & Experiments with sparse SoftMax function, where the proposed method is better than FGM
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