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:
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:
Andrew Ng’s Machine Learning Course (Coursera)
John Hopkins’s Biostatistics Bootcamp (Coursera)
A First Course in Probability, Ross, 8th edition (PDF textbook)
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:
General or All
Growing list of questions from mockinterview.io
105 Data Science Interview Questions (General, ML)
Machine Learning Questions (General)
21 Data Science Interview Questions & Answers
