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Rules of Machine Learning: | Google Developers

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This document is intended to help those with a basic knowledge of machine learning get the benefit of Google's best practices in machine learning. It presents a style for machine learning, similar to the Google C++ Style Guide and other popular guides to practical programming. If you have taken a class in machine learning, or built or worked on a machine­-learned model, then you have the necessary background to read this document. The following terms will come up repeatedly in our discussion of effective machine learning: To make great products: do machine learning like the great engineer you are, not like the great machine learning expert you aren’t. Most of the problems you will face are, in fact, engineering problems. Even with all the resources of a great machine learning expert, most of the gains come from great features, not great machine learning algorithms. So, the basic approach is: This approach will work well for a long period of time. Diverge from this approach only when th

Home Products Machine Learning Guides Rules of ML Rules of Machine Learning: Stay organized with collections Save and categorize content based on your preferences. Page Summary outlined_flag Prioritize building robust infrastructure and simple models before incorporating complex machine learning algorithms. Leverage existing heuristics and domain knowledge to enhance model performance and system intuition. Continuously iterate and refine models through feature engineering and addressing potential pitfalls like training-serving skew. Align machine learning objectives with measurable product goa

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