What do you think?
Rate this book
Inside the Machine Learning Interview: 151 Real Questions from FAANG and How to Answer Them
Let Peng Shao, a former engineering leader at Amazon and Staff ML Engineer at Twitter, be your guide to mastering Machine Learning interviews in this comprehensive 314-page resource.
Inside, you'll
Comprehensive breakdown of the ML interview process, including all the major interview ML Fundamentals, ML Coding, ML System Design, & ML Infrastructure.Proven strategies for approaching and solving a wide range of ML problems, drawing from real-world scenarios.Step-by-step guidance on tackling ML coding challenges, system design questions, and infrastructure design problems.Deep dive into the mindset of interviewers, understanding what they value and how to effectively demonstrate your expertise.Practical examples and case studies showcasing the history of solutions to ML problems, from pioneering approaches to the state of the art.
About Peng
Peng Shao has over a decade of ML leadership experience spanning diverse industries such as social media, e-commerce, and finance. He is a former Staff ML Engineer at Twitter. He was a founding team member of Amazon Alexa, where he oversaw the speech recognition services behind the Echo and Fire TV. He also spearheaded the ML and NLP development for FactSet Fundamentals, a leading fintech product, and co-founded Roxy, a venture-backed AI startup that was acquired in 2019.
Inside, you'll
Comprehensive breakdown of the ML interview process, including all the major interview ML Fundamentals, ML Coding, ML System Design, & ML Infrastructure.Proven strategies for approaching and solving a wide range of ML problems, drawing from real-world scenarios.Step-by-step guidance on tackling ML coding challenges, system design questions, and infrastructure design problems.Deep dive into the mindset of interviewers, understanding what they value and how to effectively demonstrate your expertise.Practical examples and case studies showcasing the history of solutions to ML problems, from pioneering approaches to the state of the art.
About Peng
Peng Shao has over a decade of ML leadership experience spanning diverse industries such as social media, e-commerce, and finance. He is a former Staff ML Engineer at Twitter. He was a founding team member of Amazon Alexa, where he oversaw the speech recognition services behind the Echo and Fire TV. He also spearheaded the ML and NLP development for FactSet Fundamentals, a leading fintech product, and co-founded Roxy, a venture-backed AI startup that was acquired in 2019.
398 pages, Kindle Edition
Published May 9, 2023
19 people are currently reading
30 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 2 of 2 reviews
April 10, 2025
Good book for system design
This is a very good book for beginner for system design as it balance out between going in details and explaining what is necessary. For serious ML project you might need more in depth book but this book would keep you focussed from interview perspective. You might read this book along with other ML books in order to gain maximum benefit
This is a very good book for beginner for system design as it balance out between going in details and explaining what is necessary. For serious ML project you might need more in depth book but this book would keep you focussed from interview perspective. You might read this book along with other ML books in order to gain maximum benefit
Read
August 16, 2025Inside the Machine Learning Interview” is a very useful book for anyone preparing for ML roles. At ARCQ AI, we find it especially helpful for guiding our team on real FAANG-style questions and improving how we approach machine learning problems.
For more information on how appleid this knowledge in our company at https://arcq.ai/, please don't hesitate to visit us.
For more information on how appleid this knowledge in our company at https://arcq.ai/, please don't hesitate to visit us.
Displaying 1 - 2 of 2 reviews