An affordable Arduino-based IoT setup generates real-time optical data for students to compare traversal, Bayesian, and deep learning methods in a self-driving experimental workflow.
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2 Pith papers cite this work, alongside 57 external citations. Polarity classification is still indexing.
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BASIL is a GUI application implementing Bayesian optimization for single- and multi-objective process optimization using surrogate models.
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Building an Affordable Self-Driving Lab: Practical Machine Learning Experiments for Physics Education Using Internet-of-Things
An affordable Arduino-based IoT setup generates real-time optical data for students to compare traversal, Bayesian, and deep learning methods in a self-driving experimental workflow.
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BASIL: Bayesian Application for Scientific Iteration and Learning
BASIL is a GUI application implementing Bayesian optimization for single- and multi-objective process optimization using surrogate models.