Python and ML related questions
Ml Engineer Interview Questions
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Develop a data processing script for calculating data statistics of potentiall huge data
Started with basic ML questions, like hyperparameters, feature engineering, lstm, gradient boost, k-nearest neighbours, clustering etc. Then moved onto DSA - one question on heap and another on Dynamic programming + Graph.
Salary expectations, my experience, current job..
1. Quick self introduction 2. Python assessment (you have to tell, without using IDE or AI, what will be printed for each exercise): # Exercise 1 my_str = "ABCDEFGH" print(my_str[1:3] + my_str[5:7]) # Exercise 2 import numpy as np a_1 = [1, 4] a_2 = [2, 5] dot = np.dot(a_1, a_2) print(dot) # Exercise 3 def func(a: int, b: int) -> int: return a + b try: result = func(1, "a") print(result, sep=" ") except: print("1b", sep=" ") finally: print("1c", sep=" ") # Exercise 4 def func(name): name = "A" name = "B" func(name) print(name) # Exercise 5 nums = range(1, 6) nums_modified = [x ** 2 for x in nums if x % 2 == 0] print(sum(nums_modified))
Briefly describe about the projects that you have worked on
The first interview was an orientation. The interviewer didn't ask any direct questions.
Different AI models I have used
ML basics LLM fundamentals DSA medium to hard with 10-15 minutes at max
About the llms and projects
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