@_vmlops: A guy landed offers from Google, LinkedIn, Snap, Coupang, and StitchFix during his ML interview run. That kind of insig…

A guy landed offers from Google, LinkedIn, Snap, Coupang, and StitchFix during his ML interview run. That kind of insight usually comes with a price tag. He wrote it all down and put it on GitHub for free instead That repo now has 12.4k stars, and it's basically the closest thing to a "cheat sheet" for ML interviews that actually works, because it's based on real questions he was asked, not guesses. Here's what's inside: → a study plan that tells you exactly what to focus on, so you're not wasting weeks on stuff that never comes up → leetcode and SQL practice, including the specific things interviewers keep asking (like window functions and join types) → stats and probability questions taken straight from real interviews → AB testing basics, since almost every company asks about this now → classic ML and deep learning concepts explained simply → actual system design examples, like how to design a recommendation system or a fraud detection pipeline → a reading list of papers from people like Andrew Ng and Yoshua Bengio → an FAQ section answering the questions everyone secretly wonders about, like "do I really need to solve LeetCode Hard" or "how much cloud stuff do they actually ask" It's not trying to teach you everything about machine learning. It's trying to teach you what gets asked, which honestly matters more when you're prepping under a deadline If you're getting ready for an ML or data science interview, this is worth a bookmark