Explain your past experience and what problems did you solve for
Sr Data Scientist Interview Questions
3,513 sr data scientist interview questions shared by candidates
time series outlier detection methods, etc
Preguntas técnicas sobre Python, Deep Learning, NLP, Machine Learning, OpenCV, Reinforcement Learning, Generative AI...
1. What is the difference between Batch Normalization and Layer Normalization? How do they impact training? 2. Explain the concept of attention mechanism in neural networks. How is it used in transformer models? 3. What are GANs (Generative Adversarial Networks), and how do they work? 4. Describe the concept of transfer learning. When and how would you use it? 5. What is the difference between Markov Chains and Hidden Markov Models? Provide examples of their applications. 6. How does the backpropagation algorithm work in neural networks? 7. What are the key differences between L1 and L2 regularization? In which scenarios would you use each? 8. Explain the working of a convolutional neural network (CNN). What are its primary components? 9. How does a recurrent neural network (RNN) handle sequential data? Explain vanishing and exploding gradients in RNNs. 10. Describe the process of gradient descent. What are some variations, and when would you use them?
What is one time you didn't deliver and how did you handle the result
for stat, they ask the properties of PDF, for ml, they ask assumption of Linear Reg
Preauth classification case study with code and explanations.
Pure prediction problem. Build a model given 3 fields.
How would you rate your statistics skills? How advanced are your coding skills?
What do I like about this role and what do I think are the positives and negatives of working for a company like NewDay
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