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 ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a combination of symbolic programs and neural networks. These concepts are grounded ...

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 ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

Abstract: Distributed gradient descent algorithms have come to the fore in modern machine learning, especially in parallelizing the handling of large datasets that are distributed across several ...

Abstract: In this paper, we propose an algorithmic framework for local path planning using gradient descent in complex environments, where we divide the trajectory planning problem into two aspects: ...

This file explores the working of various Gradient Descent Algorithms to reach a solution. Algorithms used are: Batch Gradient Descent, Mini Batch Gradient Descent, and Stochastic Gradient Descent ...

A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...