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10 Machine Learning Interview Questions – ANSWERED



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We cover 10 machine learning interview questions. Have you had interesting interview experiences you’d like to share? Leave them in the comments!

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REFERENCES:
[1] Interview Questions: https://www.springboard.com/blog/machine-learning-interview-questions/
[2] Generative Vs Discriminative: https://stats.stackexchange.com/questions/12421/generative-vs-discriminative
[3]: What is Bayes Rule: http://www.askamathematician.com/2011/10/q-what-is-bayes-rule-and-how-do-i-use-it-in-daily-life/
[4] The likelihood function is not PDF: https://stats.stackexchange.com/questions/31238/what-is-the-reason-that-a-likelihood-function-is-not-a-pdf
[5] Cross Validation for time series: https://robjhyndman.com/hyndsight/tscv/
[6] SMOTE: https://jair.org/index.php/jair/article/view/10302
[7] Combating Imbalanced Data: https://www.analyticsvidhya.com/blog/2017/03/imbalanced-classification-problem/
[8] Understanding ROC: https://towardsdatascience.com/understanding-auc-roc-curve-68b2303cc9c5
[9] Publicly available datasets: https://www.springboard.com/blog/free-public-data-sets-data-science-project/
[10] Probability Vs Likelihood: https://stats.stackexchange.com/questions/2641/what-is-the-difference-between-likelihood-and-probability

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16 thoughts on “10 Machine Learning Interview Questions – ANSWERED
  1. Happy 2019 everyone! Honored to have the first video on this channel! And hoping to make more here in the future. If you are interested in learning more about machine learning, deep learning, & data sciences, stop by channel to say hi 😉

  2. Just wanted to let you know I really enjoyed your video. Paused it right after you asked the question to give it a go. Didn't get that many right myself, but am taking it as a learning experience. 10 questions closer in preparation 🙂

  3. Simplest meaning of likelihood and probability are below…
    Likelihood where we get the probability when label is occurred and this probability score store into memory.
    ………………..
    And probability is used in testing phase. We are trying to predict the probability when features are true

  4. Thanks alot. This video really helped to get the idea of the type of questions and topics in an interview. Can you post a video mentioning how to prepare for an ML/DS interview(because there are so many things to study)? How to get noticed by recruiter and getting selected for an interview? Getting the interview call is very hard nowadays even after applying in so many organizations.

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