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 ...

Learn how forward propagation works in neural networks using Python! This tutorial explains the process of passing inputs ...

Abstract: Fractional-order derivatives have the potential to improve the performance of backpropagation (BP) neural networks. Several studies have found that the fractional-order gradient learning ...

Abstract: Artificial intelligence has proliferated across numerous fields of study as a result of its rapid and accurate response times. Its application in fluid dynamics for optimization and ...

Welcome to the Python Learning Roadmap in 30 Days! This project is designed to guide you through a structured 30-day journey to learn the Python programming language from scratch and master its ...

This repository implements a Feedforward Neural Network (FFNN) in Python to classify intent from the NLU Benchmark dataset. The project focuses on understanding the learning process through manual ...

Using backpropagation to compute gradients of objective functions for optimization has remained a mainstay of machine learning. Backpropagation, or reverse-mode differentiation, is a special case ...