cracking-the-data-science-interview

Why we included this project

This is a practical study companion for anyone working through data science and machine learning interview prep, not a piece of software you run. It brings together cheatsheets on the core topics interviewers tend to ask about, like SQL, statistics, probability, and the main supervised and unsupervised learning algorithms, plus a set of recommended textbooks and a question bank built from real interviews. The case studies stand out because they show how to think through building ML systems for actual business problems, which is where a lot of candidates get stuck. There is also a project portfolio covering recommendation systems, computer vision, and classical machine learning that gives you a model for how to document your own work. Treat it as a structured syllabus: you will be reading, reviewing, and drilling practice questions rather than running code.