Machine Learning Function Approximation: This code implements the fully-connected Deep Neural Network (DNN) architectures considered in the paper "The gap between theory and practice in function approximation with deep neural networks" available at https://arxiv.org/abs/2001.07523
Multi-Head ReLU Implicit Neural Representation Networks
Code for optimizing MILP problems with embedded ReLU networks
Implementing a 4 layer neural to identify digits from a 28x28 grid using just python and numpy
Text Generation
Traininig a simple neural network with ReLU activation function to classify the data.
This repository delves into the role of activation functions in perceptron-based classification models. It features a comprehensive Jupyter notebook demonstrating different activation functions, their mathematical foundations, and their impact on model performance.
This project utilizes neural networks to recognize handwritten digits (0-9) through multiclass classification, employing ReLU activation and Softmax function for accurate predictions.
Computer Vision Model for Age Estimation from Facial Images
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