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How can you ensure a dataset is free of bias?

How would you program an algorithm to simulate the roll of a non-uniform X-sided dice?

Could you produce 1000 data points in R with a normal distribution, defined mean, and variance, analyze the dataset summary, and plot its density? Also, show how to do this in a Python environment on Codility.

What are the essential elements of Naive Bayes and how do you decide on the classification threshold?

Describe a conflict situation you have experienced

Find expectations of a random variable with basic distribution. How would you construct a confidence interval? How would you estimate a probability of ordering a ride? What assumptions do you need in order to estimate this probability?

Can you explain the functional differences between CNNs and RNNs?

Can you walk me through your thought process for selecting the right algorithm for a machine learning task?

Assuming you are randomly drawing values each day from a normally distributed variable with a mean of 0 and a standard deviation of 1, what is the expected number of days it would take for you to draw a value greater than 2?

Among the ReLU and sigmoid activation functions, which one is more effective in addressing the vanishing gradient problem?