Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...
Abstract: An AC disturbance suppression method for permanent magnet synchronous motor (PMSM) drives is proposed on the basis of a mathematical optimization algorithm. First, the AC disturbances of the ...
Learn how gradient descent really works by building it step by step in Python. No libraries, no shortcuts—just pure math and code made simple. Federal judge orders Fulton County Georgia election case ...
Enhancing Gradient Descent with Parallel Computing: A Scalable Optimization Using Federated Learning
Abstract: Traditional Stochastic Gradient Descent (SGD) follows a sequential update process, which can be slow and inefficient for large-scale distributed learning tasks. Parallel computing offers a ...
1 College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi, Xinjiang, China 2 Xinjiang Key Laboratory of Water Engineering Safety and Water Disaster Prevention, Urumqi, ...
Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
The development of a high-precision displacement prediction model for landslide geological hazards is crucial for the early warning of such disasters. Landslide deformation typically exhibits a ...
Your content might be great, but if AI platforms aren’t surfacing it, your audience won’t see it. As generative search reshapes the SERP, staying visible requires more than keywords and backlinks. You ...
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