khangich/machine-learning-interview

Covers end-to-end ML interview preparation with curated case studies on real system designs (YouTube recommendations, LinkedIn feed ranking, ad prediction) drawn from FAANG production systems. Includes structured learning paths combining LeetCode practice tracking, SQL optimization, Python concurrency fundamentals, and statistical reasoning, alongside practical guidance on coding standards, data structures, and big data frameworks like Spark. Provides interview stories and success patterns from actual candidate experiences across multiple companies.

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