Deep Learning with Yacine on MSN
Deep neural network from scratch in Python – fully connected feedforward tutorial
Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...
Physics-Constrained Neural Network-Based Compact Modeling of Displacement Damage for AlGaN/GaN HEMTs
Abstract: This article proposes a physics-constrained neural network (PCNN) framework to model displacement damage-induced degradation in AlGaN/GaN high-electron-mobility transistors (HEMTs). The ...
Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive technology and inclusive education. In an attempt to close that gap, I developed a ...
In this video, we will understand forward propagation and backward propagation. Forward propagation and backward propagation in Neural Networks, is a technique we use in machine learning to train our ...
Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...
In the context of the rapid development of computer hardware and the continuous improvement of the artificial intelligence and deep learning theory, aiming at the traditional numerical solution method ...
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