机器学习 1090 Views






Hello r/MachineLearning!

I am underway with an interview for an AI research company. I’m pooling all the resources I’ve found on how to tackle the interview, as well as asking for more. What I’ve found a lot of are blog posts and video lectures. Principally, I’m trying to find good practice question & answer style posts in these subjects, the more topic specific, the better. I thought I would also share the resources I have already found to motivate visibility of the post and help people in my position.

From my research, I’ve found four main categories to study:

  • Concepts for quiz-like questions

  • Practicals for interview coding sessions

  • Machine Learning

  • I know this is a popular topic on here, so I’ll start with the discussions I found on reddit and other forums. Most of these aren’t particularly useful in general, and I will post any links inside them further on down the post. I’ve kept it to the last two years, since things move pretty quickly in data science:

    • Crash Course Materials (reddit)

    • OpenAI Advice (reddit)

    • Google Brain Advice (reddit)

    • DeepMind Advice (reddit)

    • Other post about deepmind

    I did not find a huge amount of useful material in the above posts. I did find blog posts were a good way to form an overall strategy:

    Blog Posts:

    • Crushed it: Landing a data science job

    • Stuff I’ve Messed Up While Interviewing

    • Data Science Interviews

    • How to Prepare for a Machine Learning Interview

    • Data Science Interview Questions with Answers (discussed)

    • How to Ace Data Science Interviews: Statistics

    • Common Probability Distributions: The Data Scientist’s Crib Sheet

    Lots of these posts recommended textbooks and coursera courses. I feel like these are useful if you are starting from zero or have lots of time:

    Courses & Textbooks:

    • Has self-test with answers as well

  • Statistical Inference, Casella & Berger, 2nd edition (PDF textbook)

  • Lots of people like “cheat-sheets.” I think they are a good study aide, but can be too information dense to use as primary material. I will call this “reference material.”

    Reference Material:

    • Great overview of probability distributions (blog post)

    • Python for Data Science : Keras & Numpy

    • ML Algorithm Flowchart / Cheat Sheet

    If you’re like me and are around one week out from your interview, I find question sheets as the ultimate study material, bonus points if they have answers. This guides my study and informs to what level I should know things, otherwise the amount of resource and material is overwhelming. I am really looking for more of these, please comment with some if you know where to find them, I will add them to the list.

    Question Sheets:

    • Growing list of questions from

    • 105 Data Science Interview Questions (General, ML)

    • Machine Learning Questions (General)

    • 21 Data Science Interview Questions & Answers

    • 109 Data Science Interview Questions (General, many different topics, more links inside as well)

  • Probability

    • Answers to odd questions

    • 40 Questions and Answers on Probability for Data Science (Probability)

    • Dartmouth Intro To Probability Textbook

  • Statistics

    • Need material

  • Mathematics

    • Linear Algebra, Set Theory & Algebra, Numerical Methods & Calculus, Graph Theory, Combinatorics, Propositional & First Order Logic: Multiple Choice with Answers

    • Mathematics of Machine Learning (a textbook still in development)

    • Calculus of Multivariate Optimization (lecture sheet with examples)

  • Programming

    • Cracking the Coding Interview: 150 Programming Interview Questions with Solutions (textbook pdf)

    • Computer Science Multiple Choice Questions & Answers

    • More CS Multiple Choice Questions & Answers

  • Machine Learning

    • See general section.

    • Andrew Ng’s Coursera Quizzes & Answers

  • Reinforcement Learning

    • Reinforcement Learning: An Introduction, Sutton & Barto (online textbooks with problems/solutions)

    I will edit and update this posts as I find more resources, and if you can add any, please comment!


    [D] Study Guides for Interview at AI Research Company (OpenAI, DeepMind, Google Brain, etc.). Can anyone add to my list? from MachineLearning




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