Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Department of Mechanical Engineering, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile Centro Científico Tecnológico de Valparaíso (CCTVal), Universidad Técnica Federico Santa María ...

Neurons in cortical networks are very sparsely connected; even neurons whose axons and dendrites overlap are highly unlikely to form a synaptic connection. What is the relevance of such sparse ...

Abstract: In this study, we present a novel approach to adversarial attacks for graph neural networks (GNNs), specifically addressing the unique challenges posed by graphical data. Unlike traditional ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Abstract: The article deals with the problem associated with the influence of a prompt composed by users on the efficiency of the generated program code. The aim of the research is to work out a ...