Explain linear regression and a problem on probability
Machine Learning Engineer Interview Questions
6,173 machine learning engineer interview questions shared by candidates
1. Describe your academic background and projects you have worked on. 2. If you have to classify if a bone is fractured or not, what would you do? Explain your approach. 3. What is Region of Curve, this is actually ROC-AUC, just a different terminology used for the same. 4. Explain the confusion matrix and its corresponding terminologies. 5. Would you have to make any changes to the above Model after 6 months? 6. Any projects on Unsupervised learning?
Project Experience, Machine Learning Concepts, Python Questions
Design a system to detect traffic light signals.
What are your experiences with classification? How did you design your ML pipeline?
The questions in the first technical interview will be mostly based on your resume. You will also be given a programming question.
The interview process consists of 1 aptitide + 2 technical rounds (No HR round) Aptitude round - Total of 80 questions ( 78 + 2 coding ( medium-level )) First Technical Interview :- The interviewer was very friendly and asked some basic questions about python and machine learning and AI (regularization, dropout layers etc.) and some questions regarding my project Second Technical Interview :- This interview was more focused on my work that I had done in my internships. The interviewer also asked some questions on a machine learning case study and in the end asked some easy coding questions to solve
1) Explain Decision trees, how how would a tree split numerical data.
Machine learning algorithms. Difference between bias and variance. How do you train a model from the start.
What is LSTM and GRU
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