1) Technical difference between Pyspark and Pandas 2) If you have large dataset with 1000s of features and only want some important feature, how will you identify it? 3) Dimensionality reduction? And why PCA is not an ideal solution in real world? Any other options? 4) If you have to build a model for Business partners regarding calls received by them for Opening account, paying bill and q&a? How will you design the whole ML algorithm from scratch? What features you will consider as important? How will you get the data? All steps involved till end. 5) For continuous and categorical features, which ML algorithm is best? And why?
Data Associate Interview Questions
2,713 data associate interview questions shared by candidates
Describe a time that you had to step-up
What is the other name of the sampling with replacement?
ML, NLP, Deep learning, Time series, etc.
experience with pytorch, jupyter? experience with Docker
Describe cross validation and what its main purpose is in a Data Science workflow.
Basic pillars of OOP. Given the value of a node in the linked list, dekete it
Explain Hadoop architecture. Give an example for MapReduce.
Explain Joins in SQL Given Hour and minute , Find the angle between hour hand and the minute hand in the clock
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