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 ...

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python As shutdown ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Pepe Coin price has rebounded after forming a falling wedge pattern. Zebec Network token surged after the company was invited to talk in UK parliament. Stellar Lumens (XLM) token price has surged as ...

In the field of materials science, the application of machine learning, particularly neural networks inspired by the human brain, has gained significant traction in recent years. One of the key ...

Abstract: Communication signal prediction holds great significance for the optimization and deployment of B5G networks. In this letter, we propose a neural network model with Propagation Path ...

This repository contains my implementation of a feed-forward neural network classifier in Python and Keras, trained on the Fashion-MNIST dataset. It closely follows the tutorial by The Clever ...

Abstract: Surface water quality is of utmost significance to ensure public health and facilitate sustainable economic development. Traditional water quality assessment methods are typically ...

Introduction: Most farmers in Nigeria lack knowledge of their farmland’s nutrient content, often relying on intuition for crop cultivation. Even when aware, they struggle to interpret soil information ...