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🤖 FREE · 22 CARDS

Machine Learning Interview Flashcards: Algorithms and Intuition

Short, intuitive answers to the ML questions asked in data science and ML engineer interviews.

  • 🌳 Trees and ensembles
  • 📉 Training and tuning
  • 📥 Revision download

How to use the Machine learning Interview Flashcards

  1. 1. Choose topicsPick one topic or all of them, a round size, and whether to skip cards you already know.
  2. 2. Flip and gradeRead the question, answer aloud, then reveal the answer and mark it known or still learning.
  3. 3. Review your resultsMissed cards come back later in the round. At the end see your score by topic and download the cards to revise.

What the deck covers

The deck focuses on intuition: what each algorithm does, when it fails, and how to explain it simply, which is what interviewers test. The 22 cards are grouped into 6 topics: Basics, Models, Training, Evaluation, Deep learning, Practice. Answers are short on purpose: one or two sentences you can say out loud, which you then back up with an example from your own projects.

A card from the deck

Q: Random forest vs gradient boosting?

A: A random forest trains many trees independently on random samples and features and averages them, which reduces variance. Boosting trains trees one after another, each fixing the previous errors, which reduces bias. Boosting often scores higher but needs more tuning.

Follow up by naming when you'd pick each: random forest as a strong default with little tuning, gradient boosting (XGBoost, LightGBM) when you can tune for the best score.

How to study with it

  • Draw the bias-variance picture from memory; many interviewers ask for it on a whiteboard.
  • Link each algorithm card to a dataset you've used.
  • In the Machine learning deck, cards you mark "still learning" come back three cards later in the same round, and the results screen lists them so you can download a revision sheet.

More questions from this deck

Other Machine learning questions you'll meet include:

  • Classification vs regression?
  • How does linear regression work?
  • What is PCA used for?
  • What are hyperparameters, and how do you tune them?
  • What is transfer learning?

Frequently asked questions

Is the maths covered?

Lightly. Answers give intuition and key formulas without derivations.

Are LLMs covered?

The transformer card introduces them; this deck isn't specific to LLMs.

Are the Machine learning interview flashcards free?

Yes. You can flip through every card of the Machine learning interview flashcards without signing up. When you open your results for the first time, we ask once for your name and WhatsApp number; after that the Machine learning interview flashcards and every other Uncodemy tool open straight away.

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