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In k-means or knn, we use euclidean distance to calculate the distance between nearest neighbors. Why not manhattan distance?
How do you optimize LLMs for low-latency applications?
From a long sorted list and a short 4 element sorted list, which algorithm will you use to search the long sorted list for 4 elements.
What is Inductive Logic Programming in Machine Learning?
How is knn different from k-means?
Why ensemble learning is used?
Consider a problem of preparing a schedule for a class of student. This problem is a type of a) Search Problem b) Backtrack Problem c) CSP d) Planning Problem
What background is necessary to understand and work with quantum AI?
Where can you run a Tensorflow?
How do data management procedures like missing data handling make selection bias worse?
Why do we need a validation set and test set? What is the difference between them?
what is the difference between extrapolation and interpolation?
Where linear optimization is used?
What is not represented by using propositional logic? a) Objects b) Relations c) Both a & b d) None of the mentioned
What is logistic and linear regression? How do you treat multicollinearity and heteroscedasticity in regression? Name some packages in r and python for building regression models.
