Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
Abstract: This tutorial brief shows how Artificial Neural Networks (ANNs) can be used for the optimization and automated design of analog and mixed-signal circuits. A survey of conventional and ...
This repository provides an automated code graph analysis pipeline built on jQAssistant and Neo4j. It supports Java and experimental TypeScript analysis, capturing both the structure and evolution of ...
An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley, author of the ...
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