Machine Learning Interview Questions & Answers | Machine Learning Interview Preparation |Simplilearn

This Machine Learning Interview Questions And Answers video will help you prepare for Data Science and Machine learning interviews. This video is ideal for both beginners as well as professionals who are appearing for Machine Learning or Data Science interviews. Learn what are the most important Machine Learning interview questions and answers and know what will set you apart in the interview process. This video is a part of the Machine Learning with Python Series.

Some of the important Machine Learning Interview Questions are listed below:
1. What are the different types of Machine Learning?
2. What is overfitting? And how can you avoid it?
3. What is false positive and false negative and how are they significant?
4. What are the three stages to build a model in Machine Learning?
5. What is Deep Learning?
6. What are the differences between Machine Learning and Deep Learning?
7. What are the applications of supervised Machine Learning in modern businesses?
8. What is semi-supervised Machine Learning?
9. What are the unsupervised Machine Learning techniques?
10. What is the difference between supervised and unsupervised Machine Learning?
11. What is the difference between inductive Machine Learning and deductive Machine Learning?
12. What is 'naive' in the Naive Bayes classifier?
13. What are Support Vector Machines?
14. How is Amazon able to recommend other things to buy? How does it work?
15. When will you use classification over regression?
16. How will you design an email spam filter?
17. What is Random Forest?
18. What is bias and variance in a Machine Learning model?

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[SimplilearnOfficial]

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[Jr-xshy]

Thanks so much, I have an interview tomorrow morning and this helped wrap up a few concepts!

[AishwaryaAR]

Hello! I really enjoyed watching this video. It was slowly and simply explained, with analogies and keywords. Would really appreciate it if you made a part two with advanced questions covering regression and different models (SVM, KNN... in depth) :)
Thank you!

[adityagupta]

Thank You for this video! I'm able to answer all the questions and this boosted my confidence for my upcoming interview. Thanks a lot again.

[AyushRastogi]

Please explain different algos (Logestic Regression, SVM,Decision Trees, RandomForest) with their parameters and how these parameters affects our models .

[ahmedloaiali]

perfect summary before any Machine learning interview... thx

[mau_lopez]

Great video, really useful ! Thanks a lot

[shailan]

Thank you so much for this video. It is really helpful

[markteams]

It was a quick review of main principles in Machine learning and it would be useful to brush up and summarize what you probably learned here and there about Machine Learning.

[robindong]

Thank you so much, I really enjoy this class and learned so much.

[mex]

Thank you so much. truly appreciated!!

[saurabhtripathi]

thank you bagging concept is also important to add here.

[adifull]

Question 5, at 17:45 bullet points and the pictorial view are in contradiction. Say for small data.. high bias & low variance are given in explanation whereas picture says algorithm with low bias/high variance...

[excelminutes]

Thx for the video.Please make a video on how to consider selected variables among a vast number of variables when making a regression model.What are the parameters we should look in those variables such as correlation, domain knowledge...and how should we prioritize them.

[piyushsharma]

I really enjoyed the session can you please come up with Deep learning concepts session.

[mongaslanguagetechnologies]

Very clear and detailed explaination. Thanks.

[divyanshoze]

Amazing video, vast questions put well together.

[dgstalk]

This is an excellent set of ML interview questions, however few more practical based questions should have been more helpful. I did enjoy the session very much as the explanation was given in a precise manner and easy to understand.

[Taran]

These are real basic an super easy questions... i doubt any machine learning interviews will consist many of the questions from these... maybe 1-2 just for warm up. Be prepared to face stats and prob questions... master operations with matrices...

[parthi]

your voice is going up and down its difficult to listen at any volume level