Take home project to classify winners in a chess dataset. Supposed to spend a couple hours on it.
Ml Engineer Interview Questions
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1. What does correlation mean? what is the interpretation if the correlation is 0? 2. What is collinearity, how to handle it? also for multicollinearity 3. How to evaluate regression models? explain r squared and adjusted r squared and difference between them 4. Explain regularization techniques, difference between ridge and lasso? 5. Explain working of decision trees, how to select parent and child nodes, gini impurity, etc? 6. Bagging and boosting and their difference, what is ensemble models, how to handle overfitting, explain precision recall roc curve 7. Create dictionary in python from 2 list and key values, sql query for window functions-Rank(), all joins in sql
Round 1 1 . list questions 2. biase , variance 3. resume walk through
What is the probability function of the logistic regression.
Can you explain me RAG and how it works?
Data Structure Algorithms, Behaviourial questions and resume questions
Explain Principal component analysis and code it up
Evaluate running time of the sorting algorithm by the number of common friends in social network
ML and DL Algorithm such as svm
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