Machine Learning System Design: With End-to-end Examples

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Discover the ins and outs of feature engineering, selection, and importance analysis with topics like model predictions, accuracy interpretability tradeoff, and deep learning insights. Learn how to measure and report results effectively, including A/B testing strategies, metrics selection, and result reporting. Dive into integration practices, API design, release cycles, and system operation tips. Explore the significance of monitoring and reliability, covering data quality, software hea…

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