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Devise a behavioral analytics system for fraud prevention at Yandex.

Discuss a machine learning model you have experience with and its underlying principles.

If you were tasked with optimizing hyperparameters for a machine learning model, what method would you use and why? Can you explain the differences between grid search CV and random search CV?

What is the relationship between bias and variance in machine learning, and can you give an example of how this tradeoff can be observed in a model's performance?

As the labels are known in your clustering exercise, what approaches will you take to evaluate the model's performance?

Could you enumerate some optimization algorithms that you know? What techniques would you employ to handle an optimization problem with a large number of variables? How does the simplex algorithm operate in solving optimization tasks?

Design a system for real-time processing of financial market data.

How would you define batch normalization and dropout within the context of machine learning?

Dimension reduction is an essential aspect of Machine Learning. Could you list some methods used to achieve this and their specific use cases?

Gradient issues can be frustrating in deep learning. What are your tried-and-tested techniques to manage these problems?