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Could you discuss the key assumptions that govern linear regression models and explain the significance of taking these assumptions into account when interpreting statistical results?

What's the method to determine the highest probability of k heads in n coin tosses?

Can you differentiate between type I and type II errors when conducting a hypothesis test? And if you had to pick, which error do you think is more severe?

When did you last disagree with your boss or executive?

How do you manage your work load at your current company?

Could you explain the importance of training and loss graphs for neural networks? How do various loss functions impact the shape of the loss graph, and what are some commonly known ones? What is the contrast between the training and loss graphs, and how do they assist in optimizing and maximizing model performance?

In creating a demand forecasting model for a ride-sharing service, which factors and data sources would you prioritize, and why? What steps would you take to validate the model and ensure its accuracy?

If a square grid is populated with numbers at each spot, what is the maximum cumulative value obtainable when moving from the top left to the bottom right, given the movement is limited to down or right?

What is the difference between bagging and boosting? What is the bias of bagging? And its variance? What is the bias of boosting? And its variance?

In your opinion, which applications of tf-idf are the most successful in text mining, and why?