In this issue: we look at Neural Architecture Search (NAS) and how it relates to AutoML; we explain the research paper “A Survey on Neural Architecture Search” and how it helps to understand NAS; we speak about Uber’s Ludwig toolbox that lowers the entry point for developers by enabling the training and testing of ML models that can be done without writing code.
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