"What are you most proud of in your professional life?"
Machine Learning Interviews
Machine Learning Interview Questions
"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."
8,210 machine learning interview questions shared by candidates
Describe a recent paper I wrote.
What features were used for your projects?
may be a easy level leetcode problem intent classification in QA scenarios
1. Given two nodes and one tree, find all the common ancestors of given two modes. 2. Flatten a binary tree to a linkedin list. (in place)
Once a machine learning model is in production, what do you do to maintain it?
How to design a fraud-detection system?
1. Call with the Recruiter: The questions were general and non-technical, such as "Tell me about yourself and your experience" and "Why are you interested in Ninety?" Typical questions that you'd expect from a non-technical recruiter. 2. Technical Interview: First part: I was asked to explain a sentiment analysis implementation, walking through the code line by line while thinking out loud. This included discussing how the code works, identifying the hyper-parameters, and suggesting ways to tune and improve performance. Second part: This focused on a broad range of machine learning and data science topics. Some key questions included: Explain Naive Bayes and Bayes' Theorem. How does it work? What is the Transformer architecture? Can you explain each component in detail? How is feature engineering done in Computer Vision tasks? What is the ResNet architecture, and how does it work? The interview covered both breadth and depth across ML/DL topics. Some LLM questions, involving RAG, etc. The other two interview: project that you're proud of? the challenges you face doing a project and how did you resolve it? followed by many more questions about the current project that they had and the challenges and asked me how would I approach them and my resolutions? ...
Why do you want to leave your current job?
SQL: joins, window functions python: new column assignment, string and list manipulations How does XGBoost work? step by step process with example How to represent categorical column with high cardinality How can embeddings be generated? How encoder-decoder might help in this How to find presence of multicollinearity in data? What is chi square test of independence? How to handle imbalanced classification? Why is PR auc better suited to such cases then ROC auc? How to handle large no. of classes in multiclass classification? What is negative sampling and how does it help in such scenarios?
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