What is feature engineering? What is back propagation?
Applied Scientist Interview Questions
1,175 applied scientist interview questions shared by candidates
How do Support Vector Machines work?
They asked about statistical methods.
What is difference between DNS and RANS in CFD
Technical question: Four dices at beginning. Throw them at each round and remove the one as long as 6 is obtained. How many rounds it take to remove all dices ?
I was asked about my research directions in my post grad studies.
Zig-zag traversal of tree, time and space complexity. What is better to use tree of graph in such case. Difference between BERT and LSTM and which will be faster
ML basic questions include evaluation metrics, data processing/augmentation related, etc
questions focused on practical machine learning skills. Topics include experience with LightGBM, neural networks, and handling large datasets. Advanced techniques like word embeddings and model evaluation methods, such as overfitting prevention and hyperparameter tuning, are discussed.
What is Heteroscedasticity and how would you model it?
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