: While primarily focused on traditional systems, this repository offers fundamental knowledge on databases, caching, load balancers, and microservices that underpin ML deployments.
Ingestion, storage, and feature engineering. machine learning system design interview alex xu pdf github
+------------------------------------------------------------+ | 1. Problem Clarification & Business Metrics | +------------------------------------------------------------+ | v +------------------------------------------------------------+ | 2. Data Engineering & Pipeline Design | +------------------------------------------------------------+ | v +------------------------------------------------------------+ | 3. Model Architecture & Feature Engineering | +------------------------------------------------------------+ | v +------------------------------------------------------------+ | 4. Evaluation (Offline Metrics vs. Online A/B Testing) | +------------------------------------------------------------+ | v +------------------------------------------------------------+ | 5. Deployment, Scaling & Monitoring (Drift Detection) | +------------------------------------------------------------+ 1. Problem Clarification and Requirements : While primarily focused on traditional systems, this
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