This blog post is the continuation of “Active Learning, part 1: the Theory”, with a focus on how to apply the said theory to an image classification task with PyTorch. Read more
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Machine learning has become an incredibly popular field of research in the last few years. While there's no shortage of libraries and tutorials in languages ...
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The following outline is a talk I gave at the Utah Ruby Users Group (URUG) where I discussed machine learning and how it can be applied in the Ruby programmi... (more…)
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For years, researchers have been trying to figure out how the human brain organizes language – what happens in the brain when a person is presented with a... (more…)
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Get to know the ML landscape through this practical, concise overview of modern machine learning algorithms. Plus, we'll discuss the tradeoffs of each. (more…)
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The workflow for building machine learning models often ends at the evaluation stage: you have achieved an acceptable accuracy, and “ta-da! Mission Accomplished.”... (more…)
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