Abstract: Deep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art ...

Abstract: Reliable fault diagnosis in power transformers is paramount for ensuring grid stability and safeguarding critical assets. This paper proposes a novel deep learning-based diagnostic framework ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Build the AdamW optimizer from scratch in Python. Learn how it improves training stability and generalization in deep learning models. #AdamW #DeepLearning #PythonTutorial ...

The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...