Business Case where we need to propose a solution for a problem using machine learning.
Sr Data Scientist Interview Questions
3,392 sr data scientist interview questions shared by candidates
Use case on classical ML stuff
How to evaluate ML models?
How many experience do you have with java, R, python....?
Everything from project
Coding standards they asked from python.
Explain the difference between bagging and boosting
How do Decision Trees, Random Forest and XGBoost differ?
Pure prediction problem. Build a model given 3 fields.
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?
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