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‘Learning representations by back-propagating errors’, written by two cognitive scientists from the University of California San Diego, David Rumelhart and Ronald Williams, and a computer scientist from Carnegie Mellon, Geoffrey Hinton,
Grace Lindsay • Models of the Mind
and prototypes, but we can also reason about concepts relative to the theories they are embedded in,
Ernest Davis • Rebooting AI: Building Artificial Intelligence We Can Trust
Then, based on the outcomes of those decisions, the algorithm adjusts, aiming for better accuracy next time.
ModernMind Publications • Generative AI for Beginners Made Easy: Master Artificial Intelligence and Machine Learning Fundamentals, Learn Creative AI, and Enhance Your Skills With Interactive Real-World Exercises
Decision trees and nearest neighbors algorithms are examples of this category.
Suresh Samudrala • Machine Intelligence : Demystifying Machine Learning, Neural Networks and Deep Learning
K-Means Clustering: An Explorable Explainer
k-means-explorable.vercel.app