While traditional data analysis often involves simpler models, future ML engineers must understand deep learning architectures like CNNs, RNNs, and transformers. Transfer learning, which leverages pre-trained models for new tasks, is a powerful technique to reduce training time and data requirements—knowledge that aspiring engineers should actively acquire.
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