/mle-ds-swe-cheat-sheets

Primary LanguageJupyter Notebook

Resources To Secure Your Next MLE / DS / SWE Job!

This repo contains cheat sheets + data structures & algorithms templates useful for MLE, DS, and SWE interviews. All cheat sheets were created by me and helped me secure multiple offers at big tech companies. If any of these resources prove helpful to you, consider leaving the repo a ⭐!

Cheat Sheets

  • Statistics: Basic statistical concepts (e.g. probability, hypothesis testing, bayesian vs frequentist etc.)
  • A/B Testing: 4 step process to approach "design an experiment" interview questions
  • Metrics Cases: Tips for data science metrics/product interviews like "why are friend requests down 10%"
  • ML Theory: Details on the general ML modeling process (e.g. cross validation, precision vs recall, etc.)
  • ML Models: Details on popular classical ML models (e.g. pros & cons, assumptions, formulas, etc.)
  • DL Models: Coming soon
  • ML Models Code: Python code for popular classical ML models (most of code from MLfromScratch)
  • ML System Design: 4 step process to approach "design a model" interview questions
  • Recommender Systems: Coming soon
  • ML Infrastructure: Coming soon
  • System Design: 4 step system design process and general topics (e.g. load balancing, caching, etc.)

LeetCode Templates

Note, the goal of these templates isn’t so much as to teach you the algorithms but more so to give you a repeatable template to use for common interview topics.