They asked me to implement a sparse matrix from scratch, without relying on any existing matrix or linear algebra libraries. This required designing an efficient internal data structure to store only the non-zero elements, rather than allocating memory for the entire matrix. In addition to the core representation, I needed to implement both addition and multiplication operations, making sure they handled sparsity correctly, maintained good performance, and produced accurate results even when matrices had different sparsity patterns.
Data Scientist Machine Learning Interview Questions
467 data scientist machine learning interview questions shared by candidates
Python coding - fetch longest palindromic substring
ML and coding . No questions on cultural fit.
Topological sorting problems on LC
Similar to implement a recommender system.
what is overfitting?
bias and variance trade-off
They asked questions on projects. "why did you use a certain machine learning algorithms, and why not another one?
1. The famous celebrity question that uses hashmap 2. Adding two linked list and storing the output in another linked list 3. Dynamic programming question
My background -- nothing specific
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