Box8 Data Analyst Interview Questions | Day 15

We have covered few interview Questions asked in Amazon, Myntra, and some of the case studies – You can get the complete list of Daily Quiz here
http://thedatamonk.com/daily-quiz/
Today is Day 15 and we will look into Box8 Data Analyst Interview Questions.
I interviewed for Data Analyst position last year at Box8, the process was smooth. Following are some of the questions asked in different rounds of recruitment. I had a couple of projects on Natural Language Processing, so the questions were mostly around NLP concepts
Box8 Data Analyst Interview Questions

Split Paragraph – http://thedatamonk.com/question/box8-write-a-regular-expression-to-split-a-paragraph-every-time-it-finds-an-exclamation-mark/
Regular Expression Output – http://thedatamonk.com/question/box8-find-the-output-of-the-following-code/
Tokenization – http://thedatamonk.com/question/box8-what-is-tokenization-and-what-are-the-important-nltk-tokenizer/
RegEx to match commas and spaces – http://thedatamonk.com/question/box8-how-to-write-a-regex-to-match-spaces-or-commas/
Ranking in SQL – http://thedatamonk.com/question/box8-ranking-in-sql/
Processing time in SQL – http://thedatamonk.com/question/box8-sql-query/
Topic Modeling in NLP – http://thedatamonk.com/question/box8-what-is-topic-modeling/
Bag of Words – http://thedatamonk.com/question/box8-what-is-bag-of-words/
RegEx in SQL – http://thedatamonk.com/question/box8-regular-expression-in-sql/
RegEx in SQL – http://thedatamonk.com/question/box8-sql-query-on-regular-expression/

You can also get the pdf of our book on ‘Natural Language Processing in Python’ directly TheDataMonk/">here

Try to answer all these questions by yourself or with the help of google 😛

In order to practice more courses on Data Science, we definitely recommend Data Camp

Practice all the questions posted over here, try to make sure that you attempt the questions. we evaluate answers every now and then and provide particular feedback on your performace

If you want any guidance or want to make a career in Data Science, then you can take a look on our proposed Data science path

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Keep Learning 🙂

The Data Monk