Modeling Libraries Don’t Matter
Read OriginalA machine learning engineer reflects on the initial anxiety over choosing ML frameworks like PyTorch or TensorFlow, concluding that the modeling library itself is a minor concern. The real challenges lie in data pipelines, productionization, value alignment, and infrastructure that allows models to be 'plug and play.' The article emphasizes that developers can adapt to new libraries, but a solid engineering foundation is what truly matters for successful ML projects.
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