India's Most Futuristic AI Conference Is Back – Bigger, Sharper, Bolder
Most real ML systems are built around product decisions. A feed system decides what to show. A fraud system decides what to block. A search system decides what to rank. This article walks through 10 such problems in a practical interview style.
Start with the product goal. Every ML system is built to make a decision. A feed system decides which post to show. A fraud system decides whether a payment is risky. A search system decides which products should appear first.
Once the goal is clear, define success. Do not only talk about model metrics. A good ML system design answer should cover three types of metrics:
Source: Analytics Vidhya - interview questions — Read the full article on the original site ↗