Real-World AI Case Studies and System Design

21 lessons in AI Fundamentals

• Lessons From Real ML DeploymentsSlides / Video
• Multi-Stage Pipeline DesignSlides / Video
• Structuring ML Design Interview AnswersSlides / Video
• Model Selection for Production ConstraintsSlides / Video
• Handling the Cold-Start ProblemSlides / Video
• Feedback Loops in Deployed AISlides / Video
• Training vs Serving Path SeparationSlides / Video
• Estimating Scale in ML SystemsSlides / Video
• A/B Testing for ML SystemsSlides / Video
• Online vs Offline MetricsSlides / Video
• Data Collection and Labeling StrategySlides / Video
• Two-Tower Retrieval ArchitectureSlides / Video
• Retrieval-then-Ranking ArchitectureSlides / Video
• Fraud Detection System Case StudySlides / Video
• Ad Click-Through Rate PredictionSlides / Video
• Feed Ranking System Case StudySlides / Video
• Search Ranking System DesignSlides / Video
• Recommendation System DesignSlides / Video
• ML Requirements: Functional vs Non-FunctionalSlides / Video
• Framing Business Problems as MLSlides / Video
• ML System Design FrameworkSlides / Video