“In your machine-learning project, how much time will you typically spend on data preparation and transformation?” asks a 2022 Google course on the Foundations of Machine Learning (ML). Even with a machine-learning expert, selecting the appropriate model, formatting the dataset for the model, then fine-tuning it can dramatically change how the model performs, and takes a lot of work. Recruiting machine-learning researchers can be a time-consuming and financially costly process for science and engineering labs. An open-access paper on their proposed solution, called BioAutoMATED, was published on June 21 in Cell Systems. Jim Collins, the Termeer Professor of Medical Engineering and Science in the Department of Biological Engineering at MIT and the life sciences faculty lead at the Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic), along with a number of colleagues decided to tackle this problem when facing a similar conundrum. Is it possible to build machine-learning models without machine-learning expertise?
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