Course Content
ML Design Basics
This topics covers the fundamentals of Machine Learning System Design in real world.
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Requirements and Business objectives
Data Basics
Training Data
Feature Engineering
Feature Engineering II
Model Development and offline evaluation
Model deployment
Monitoring
Test in production
Infrastructure and tooling
User Experience
Interview Expectations
This topic talks about the expectations and focus areas in the interview and shares some insights into what kind of signals the interviewer captures during the interview.
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Introduction
Problem Navigation
Training Data
Feature Engineering
Model Development
Model Evaluation
Model Deployment
Questions
This topics goes through some example questions and how to approach them.
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Restaurant recommender
YouTube recommendations
ChatGPT
Bad advertisement content
Facebook news feed
Machine Learning System Design
About Lesson

A number of tech companies use Machine Learning System Design interviews to assess the candidate’s ability to handle open-ended Machine Learning problems and to design a well-structured system to handle these problems. 

In this section, we go over the main areas the interviewers are assessing the candidates on and discuss the expectations in each of these areas.

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