Acing the Python Data Science Interview Questions

[@siddharthdedhia11]

7:18 for the impatient

[@gauravchatterjee794]

5 buckets: 1. Statistical and distribution based questions 2. Probability simulation 3. String parsing, data manipulation, text processing 4. Numpy functions and matrices 5. Pandas data munging

[@rudroroy1054]

Why do companies not understand this? I was asked to have a good hacker rank score for a data analyst position. I don't mind coding but if I have good hacker rank score why would I wanna apply for a data analyst position.

[@nicholaslipanovich827]

As a Full-Stack Data Scientist the tools I use in order of preference are SQL->Pandas->NumPy. Basically I only use NumPy if I have to (e.g. when using Scikit-learn for modeling). Also PySpark, Dask, and Joblib are super important Python Big Data tools to learn.

[@pradeepdjain]

You should create a similar video for SQL

[@jameshizon4861]

Thank you. I wish I had viewed this prior to other past interviews to have a general idea of what to expect.

[@Kandyfrom1986]

Thanks for the video. Visualization also plays an important role. I am a bit surprised that it is not a part of those many interview questions that you went through

[@only_dejavu6889]

Very solid content! I definitely use Pandas more often than Numpy.

[@raykwon6174]

Very clear delivery, so much helpful info

[@pushkarajpalnitkar1695]

Thanks for the video. Very helpful. Cleared many doubts.

[@Nimmi_bro]

Also many companies wants you to know concept code and logic building, they even expand it to pyspark and sql, now it has become difficult to crack some interview because topics have become vast

[@pauls60r]

I mainly want to point out that this video is awesome and the advice is helpful. I can also tell you probably spent a lot of time stitching the video together but I honestly think it's more unnatural than having pauses and having a natural flow in speech. Just my 2 cents, I think the video would sound better and you'd save time! Subbed and following all the same.

[@observer698]

I can't find python int. questions for machine learning engineers at facebook other than the leetcode questions?

[@jeremynx]

Thank you for your videos! helps a lot.

[@iqjayfeng]

You're very welcome!

[@learnanalyticsorg]

Thanks for sharing Data Science Jay !!!

[@aidanberry6311]

Great video!

[@junqichen6241]

Great content. Thanks for sharing!

[@jessicafb5398]

Love your channel! Thank you

[@asaphakeim3614]

Awesome video this was very helpful!

[@DatascienceConcepts]

Good collection of questions !

[@alexiskerr5161]

Thank you for interview query!!!

[@chtdv]

This channel is legit!

[@prajwal2477]

That one guy who disliked this video must be hating his life.

[@iqjayfeng]

Thanks for tuning in! If you're interested in learning more about Python, be sure to check out our course. It's designed to help you master the key concepts and skills needed to excel in Python. www.interviewquery.com/learning-paths/python

[@zodiac154]

Lol lol I recently got into data science and i use Pandas way more often than numpy and I was always asking myself when this might be a problem.

[@moniquemarinslp]

Because numpy is fast..

[@yugiohsc]

The Facebook example aged well haha

[@vamsi8708]

Useless

[@fiddlepants5947]

What do you use instead of numpy then?

[@fiddlepants5947]

@@ajinkyabhavik341 what happens when you need to invoke some calculus in an optimization algorithm?

[@fiddlepants5947]

@@ajinkyabhavik341 Ok. So what do you use then?

[@fiddlepants5947]

@@ajinkyabhavik341 because I use numpy 😂

[@fiddlepants5947]

@@ajinkyabhavik341 and I misread your comment I think haha

[@sammyj29]

Great content! Thanks for sharing!