Easy to medium Python and SQL in 1st round, In 2nd round i was asked to write sql query for a join type question and to check whether a number is palindrome or not in python, What is LLM, Basics of AI/ML
Ml Engineer Interview Questions
1,795 ml engineer interview questions shared by candidates
Data Science, API, SQL, Final year projects
- Simple code to requirements question involving industry theme
Coding, design, and ml coding
1- interview question on project whatever you mention on resume. 2-role & responsibility in the current project. 3-basic question on Python & Py spark. a- pyspark coding question on basic understanding. define a model building in pyspark. b- difference bt map reduce and pyspark. c- why pyspark used instead on pandas? 4- coding questions on the list, indexing, and a-how to convert a number into an Indian currency format. (1234567) to (12,34,567) b-slicing on the list. c- one list within tuple format and how to be sorted on ascending order. Let come to domain knowledge -> 1- difference b/t linear regression and decision tree 2- define decision tree 3- use of Gini index in the decision tree. 4-why you using a decision tree over linear or logistics regression? 5-question on ChatGPT as i have mention ChatGPT. use of ChatGPT on real time, 6-difference b/t ChatGPT and Bert. 7 - one scenario case question on NLP, if i want to predict a word on the question (i want to _______ ) , which techniques use for that? 8- question on deep learning. - difference b/t dl & ml & ai. 9- difference b/t data scientist & ml engineer. 10- types of ml (supervised, unsupervised & semi-supervised & reinforcement learning). some examples of that. 11- CNN, computer vision, OpenCV, etc. 12- one business use case on (100, 200, 300, 500 & 1 cr ) how use central tendency (mean , median , mode) - how to get an outlier, how to handle missing value, mean affected the outlier & why, why they are using median over mean & why, where to use mode. 13- evaluation metrics & types & difference bt them. - recall & precision .
Questions on my current and past projects on AI/ML and other technologies.
What's the most recent and most tricky project you've worked with?
How do stay relevant with latest advancements
What is the latest progress in machine learning that has piqued your interest?
How does Gradient decent work?
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