Global Data & AI Virtual Tech Conference (GDAI 2025), the biggest virtual tech conference organized by DataGlobal Hub, was concluded with resounding success, uniting participants from various ...

Summary: Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks. Unlike traditional methods that only cluster nodes, this approach groups ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back Propagation in Neural Networks. In this video, we are using using binary ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...

Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudziądzka 5, 87-100 Toruń, Poland ...

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...

According to DeepLearning.AI, neural networks have played a pivotal role in the evolution of artificial intelligence, beginning with attempts to replicate the human brain in the 1950s. Early neural ...

This project demonstrates a minimal working implementation of a feedforward neural network using just NumPy. It’s designed for learners who want to understand the core logic of forward propagation, ...