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How would you execute a dot product computation for sparse matrices?

Please share an experience where you had to manage a conflict.

How does information theory serve in the comparison of language models? Provide an instance of how you might apply this in practice.

Please share the strategies you have applied to detect outliers in your data science endeavors.,

I would like to hear a story about a time you were challenged in public.

When assessing a model's performance, how do you decide between using a confusion matrix or an ROC curve?

In what scenarios is an ROC curve most useful? Could you explain the difference in approach between bagging and boosting algorithms?

What steps would you take to generate 1000 normal distribution data points with mean=x, variance=y in R, summarize the data, and plot the density? Then, how would you achieve the same outcome using Python in the Codility code editor?

What insights have you gained from working with tools like TensorFlow or PyTorch?

What is the probability that 2X is greater than Y, when X and Y are independent random variables having uniform distributions with mean 0 and standard deviation 1?