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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
Has anyone else begun to resent data science?
What is a data lake in basic terms?
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It involves 2 python and 2 sql questions which needs to be solved in 120 mins. I was able to solve all pass all test cases except for 1 test case in last python question. Later got invited for final rounds
I am also doing a DE assessment, would love to learn more!
So I took the data science test and it was purely Python3 based. To be fair, I did not check the possibility to switch to other languages, it could be the case.
Structure is the following:
1. Algorithmic question (similar to the hackerrank practice questions in the algorithmic section)
2. Model
3. Model with more data
My recommendation is to manage your time well (2hrs in total) and get used to the hackerrank UI before you take the test. I wrote and tested my code in my preferred interpreter with dummy data and pasted the solution into the UI to run it against the test cases later. It also seemed that the code was evaluated by a person and not purely by passing/failing test cases.
What was the modelling question like - ... was the modelling questions on QuantHub
Edit: I DMed D1 who took the coding test for Data Engineering.
Planning on taking the Data Science test soon. Will post an update.
Have you taken the test yet?
For those following the thread: I went through the technical screening. My advice: inform yourself on glassdoor about the questions asked in previous interviews. This covered 60-70% of my questions. Be prepared to know the concepts deeply and able to differentiate between methods and algorithms. I allowed myself to “spice in” some additional concepts where appropriate. For example, when asked about an algorithm I explained which limitations it has and how to solve it through e.g. data prep.
Yes
Did they had the webcam turned on?
Hi, I am giving hackerrank test for data engineer next week.
Kindly suggest on what areas should I be prepared with.
hello, care to share what type of questions are asked?
Can someone Help me in the practice for the QB Data Science test, I need some clarity on the Algorithmic questions and type of modelling question(whether it would be a Time Series Problem, multiple Linear Regression or so on)?