Career

100+ curated questions: bias-variance, regularization, neural networks, backprop, CNNs, RNNs. 11.6k GitHub stars. Includes ML system design cases: YouTube recs, LinkedIn feed, ad CTR. Author received NVIDIA, Microsoft, Amazon offers.

6 structured chapters: algorithms, ML coding, fundamentals, system design, behavioral. Updated 2025 with Agentic AI chapter. Author received offers from Meta, Google, Amazon, Apple. MIT licensed.

200+ questions across math, CS, ML workflows, algorithms. Difficulty tagged. 30 systems design questions. Companion answers at github.com/zafstojano/ml-interview-questions-and-answers. The book is FREE online.

47 free lessons covering complete ML lifecycle: product design, data prep, feature engineering, training, serving, monitoring, CI/CD, testing. 30k GitHub stars. Includes working code from laptop to distributed cluster.

Amazon Principal Applied Scientist. Deep articles on feature stores, real-time retrieval, ML testing. His applied-ml repo has 600+ curated papers from Netflix, Spotify, Pinterest. Co-authored 'A Year of Building with LLMs' (O'Reilly).

Same author as Chip Huyen's book, same content. Free lecture notes: ML production, training data, feature engineering, deployment, monitoring. Guest tutorials from Made With ML, Stitch Fix. 24 final project demos on YouTube.

6-step framework with timing recommendations. Free worked examples: Video Recommendations, Harmful Content Detection, Bot Detection. Written by former Meta and Amazon hiring managers.

6 complete ML system design cases: YouTube recommendations, LinkedIn feed ranking, ad click prediction, delivery time estimation, Airbnb search ranking. Links to source company engineering blogs.

Structured 9-step formula: problem clarification, data requirements, ML objective, offline/online metrics, feature engineering, candidate generation → ranking → filters, training data, architecture, serving/deployment.

Essential ML system design book by Chip Huyen. Based on Stanford CS 329S.

7-step framework with 10 detailed solutions: visual search, video recommendation, ad prediction.

200+ curated links: probability/stats (40+ questions), SQL, ML algorithms, real case studies, FAANG-specific prep, deep learning (40+ questions), NLP (30+ questions), Spark (55+ questions), GenAI topics.

Downloadable cheatsheets (SQL, stats, ML/DL), question bank with '150 Essential DS Questions' PDF, case studies, portfolio examples. Closest structural equivalent to the book. 4.4k GitHub stars.

100+ free practice questions: SQL, Python, statistics, ML, probability. Same author as 'Ace the Data Science Interview'. 60+ SQL from FAANG with solutions. Interactive PostgreSQL environment. Free 9-day crash course.

Interactive quizzes on ROW_NUMBER, RANK, LAG/LEAD. Consistently tested in interviews.

Company-specific SQL filtering for Airbnb, Uber, Netflix. Real interview questions with solutions.

Data science interview platform with SQL, Python, and ML questions. Take-home challenges included.

Free SQL practice with FAANG questions. Created by ex-Facebook authors of Ace the Data Science Interview.

Written by ex-Amazon Bar Raiser. Sent by recruiters to candidates. 100+ candidates credit it for getting hired.

Insights from 500+ mock Amazon behavioral interviews. STARI method with Action at 50-60%.

Googleyness traits: comfort with ambiguity, bias for action, intellectual humility.

Official 16 principles with explanations. Customer Obsession, Ownership, Invent and Simplify, etc.

Ultimate guide to business case interviews. AARRR framework, metrics, diagnostic approaches.

Three games framework: Attention, Transaction, Productivity. Real examples from Facebook, Airbnb, Spotify.

31 leaked Meta interview questions. Product sense and SQL focus.