In this video, we’ll compare data science interview questions between FAANG and non-FAANG companies to uncover the differences. This is a continuation of our previous video 'Analysis of 900 Data Science Interview Questions' ([ Ссылка ]) where we analyzed 900 data science interview questions collected from various sites over the last few years. Now let’s take the same 900 questions and split them into FAANG and non-FAANG companies.
Link to the questions:
Question by Facebook (Investigate the Discrepancy): [ Ссылка ]
Question by Facebook (Users Activity Per Month Day): [ Ссылка ]
Question by Google (Common Friends Friend): [ Ссылка ]
Question by Google (Highly Correlated Predictors): [ Ссылка ]
Question by Amazon (Neural Network and Logistic Regression): [ Ссылка ]
Question by Amazon (Random Bucketing): [ Ссылка ]
Question by Apple (Users in Meaningful Segments): [ Ссылка ]
Link to the complete blog: [ Ссылка ]
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👉 Subscribe to my channel: [ Ссылка ]
👉 Playlist for more data science interview questions and answers: [ Ссылка ]
👉 Playlist for data science interview tips: [ Ссылка ]
👉 Practice more real data science interview questions: [ Ссылка ]
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Timeline:
Intro: (0:00)
FAANG vs Non-FAANG: (1:08)
Facebook: (3:30)
Google: (5:40)
Amazon: (7:17)
Apple: (9:01)
Conclusion: (10:45)
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If you want interview practice with real data science interview questions, visit [ Ссылка ]. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, you can use ss15 for a 15% discount on the premium plans.
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Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
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#DataScience #DataScienceInterviewQuestions
