From deep research to image generation, better prompts unlock better outcomes. Here's the step-by-step formula.

A marriage of formal methods and LLMs seeks to harness the strengths of both.

Looking back at 2025, it’s obviously, on a daily basis, why the broadcast networks are dismissed by most Americans as a source of daily advertising for one side of the political debate. This tilt has ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Introduction: Electroencephalography (EEG)-based mental stress detection has the potential to be applied in diverse real-world scenarios, including workplace safety, mental health monitoring, and ...

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 ...

This academic seminar series explores a broad range of topics such as data science, urban planning and urban networks and ...

School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai, India Introduction: In recent years, Deep Learning (DL) architectures such as Convolutional Neural Network (CNN) ...

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 ...

Abstract: This work investigates the generalization behavior of deep neural networks (DNNs), focusing on the phenomenon of “fooling examples,” where DNNs confidently classify inputs that appear random ...