"To get a job in machine learning, you must have the programming and mathematical knowledge to create artificial intelligence that is capable of learning new tasks without being explicitly coded. In an interview you may be asked about your experience with pertinent coding languages such as Java and C++ as well as with writing algorithms. The interview will be comprised mainly of technical questions that test your knowledge of the fundamental concepts of machine learning such as data mining and signal processing."
First round was an Test including MCQ on ML,DL,NLP and coding question on Python and SQL . I cracked through the first and got the call by HR after few hours. Second round was schedule immediately after a day ,that was Technical round. First he asked to introduce myself through the resume and asked very basic quesions. I answered 95% of them still got the mail on second working day that they could not chosen me. Absolutely unhappy. don't waste your time for this organisation
What is your favorite machine learning algorithm? Tell me about how to handle an imbalanced dataset?
Explain the project you did in depth
When using OpenAI Apis why would you use Kubernetes, is AWS lambda a good option here?
a hard question about hyperplane projections, the probability of two dices summing 6 and effect of confounders in a linear regression.
Q: Describe the "bias-variance tradeoff"
How you identify/select which ML algorithm will suit the given problem.
Is dropout ever used at inference time.
Most related to my PhD thesis
Question I asked ML6 members: Did any of you read this paper or are familiar with the methods?
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