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Illustrate how the Monte Carlo method can estimate the value of Pi.

What aligns Airbnb with your long-term vision

What is your experience with NLP mechanisms, including recommender systems.

What do the training and loss graphs represent in the realm of neural networks? How do different loss functions affect the shape of the loss graph, and what are some frequently used ones? How do the training and loss graphs differ, and how do they play a crucial role in optimizing and improving model performance?

How would you go about writing a function that outputs all of the prime numbers beneath N?

How many and what types of loss functions have you come across in your experience?

Why do you want to work at Airbnb?

Could you provide an analogy that would help a non-technical person understand the P-value?

How can you explain k-means clustering and its effectiveness in finding a global optimum? Provide an implementation for an N*D matrix input.

In the field of machine learning, what do we mean by overfitting and underfitting? Why is it necessary to keep these phenomena in mind during model development?