This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

PPA constraints need to be paired with real workloads, but they also need to be flexible to account for future changes.

If you use consumer AI systems, you have likely experienced something like AI "brain fog": You are well into a conversation ...

For more than a century, scientists have wondered why physical structures like blood vessels, neurons, tree branches, and other biological networks look the way they do. The prevailing theory held ...

Natural physical networks are continuous, three-dimensional objects, like the small mathematical model displayed here. Researchers have found that physical networks in living systems follow rules ...

Abstract: Several studies have analyzed traffic patterns using Vehicle Detector (VD) and Global Positioning System (GPS) data. VD records the speed of vehicles passing through detectors, GPS data ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

This system uses a neural network to predict NBA game outcomes and total points, with integrated betting strategy tools including Expected Value calculation and Kelly Criterion bet sizing.

CATS-Net (Concept Abstraction and Task-Solving Network) is a comprehensive framework for understanding and implementing concept abstraction in neural networks. The system combines supervised learning ...