• This is probably the best starting point I found for ML-specific interviews (whether its internships/ full time): https://huyenchip.com/ml-interviews-book/ . Talks about the process in detail too, in addition to practice questions.
• Andrej Karpathy’s course : Neural Networks: Zero to Hero
• Hager Rady’s (U of A / Amii alumna) Interview prep guide for research positions.
• Grokking the Machine Learning Interview
• Repo of papers & tech blogs by companies sharing their work on data science & machine learning in production
• Math for ML textbook
• For probability/stats review: check out section 1 of the Deep Learning Book and chapter 2 of elements of statistical learning.
• Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI
• For cheatsheets and all sorts of interview practice for ML interviews: https://github.com/khangich/machine-learning-interview
• Lyft had a blog for Data Science interviews here.
• Navigate Through the Current AI Job Market: A Retrospect
• A deck of slides with resources for MLE/Data Science interviews by a Research Science Manager at Google.
• List of ML Youtube courses
• Data Science interview questions collection. 800+ Q & As.
• MLOps guide by Chip Huyen