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I was interviewed before Sep 2020.
Round duration - 60 Minutes
Round difficulty - Medium
It was a mix round. Starting with problem-solving, then data structures, then DBMS, and finally data science
2 Interviewers
Early morning
We will run a breadth-first search(BFS), keeping states as water present in both the jugs. We will visit all the states, keeping a hashmap for visited states to not revisit the same state. If we reach a state such that the capacity of water in one of the jugs is equal to ‘Z’ liters or the sum of water in both the jugs is equal to ‘Z’ liters we return true else we return false.
Below is the detailed ...
Balls picking probability problem
For solving this problem, we will use the fundamental concept of Insertion Sort i.e, to divide the input array into an unsorted and sorted partition. After that, keep placing elements from the unsorted partition into its correct position in the sorted partition. We will make use of pointers to keep track of various positions in both the lists and modify these po...
Keys and their properties
Some data science topic question like the difference between loc and iloc, what are dashboards etc
Round duration - 15 Minutes
Round difficulty - Easy
Early morning
Relaxed environment
Very kind and gentle
Why should we hire you?
What is your greatest achievement?
Tip 1 : Excellent communication skills required
Tip 2 : Focus on data science and data analysis
Tip 1 : Data Science knowledge and projects
Tip 2 : True and crisp information
A Transformer is a type of deep learning model that uses attention mechanisms to improve the efficiency of sequence-to-sequence tasks.
Utilizes self-attention mechanism to weigh the importance of different input elements
Commonly used in natural language processing tasks such as machine translation and text generation
Examples include BERT, GPT, and Transformer-XL
based on 1 review
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