Chip Huyen is a Stanford Graduate and former lecturer with ML experience working at top companies like Nvidia and Netlfix. She also wrote the book "Designing Machine Learning Systems", which is an Amazon #1 bestseller. Whether you want to become an ML engineer, a platform engineer, a research scientist, or you want to do ML but don’t yet know the differences among those titles, I hope that this book will serve as your guide. Highlights: - A detailed guide based on real interview experiences from top tech companies and startups. - Insights from both the candidate's and interviewer's perspectives. - Contributions from industry professionals involved in hiring at companies like Google, NVIDIA, Snap, Netflix, Primer AI, and Snorkel AI. Key Features: - Part 1: Overview of ML interview process, roles, required skills, and preparation tips. - Part 2: Knowledge questions with difficulty levels, addressing key ML concepts. - Additional Resources: Links to a web-friendly version of the book, source code on GitHub, and a Discord server for discussion. - Real-world Insights: Practical advice from an author with extensive experience as both a candidate and interviewer in the ML field. Benefits: - Learn about the ML interview process, types of ML roles, required skills, common questions, and preparation strategies. - Access to over 200 knowledge questions covering essential ML concepts and common misconceptions. - Open-ended questions to test practical problem-solving skills and experience in implementing ML models. - Resources to identify and strengthen weak areas in ML knowledge