Deep Learning - Deep Neural Network for Beginners Using Python - Problem to Solve Part 2

The video tutorial discusses decision-making in hiring based on data points. It highlights the importance of having sufficient data to make accurate decisions and examines past hiring decisions using academic and test scores. The tutorial also addresses how to handle ambiguous cases where data points lie on decision boundaries, emphasizing the need for more data to resolve such uncertainties.

Why is it not sufficient to make hiring decisions based on just two data points?

• Because two points are too close to each other.

• Because two points can lead to a good decision.

• Because two points cannot capture the complexity of the decision.

• Because two points are always enough for decision-making.

What does the presence of more data help with in the hiring process?

• It increases the hiring cost.

• It helps in making more informed decisions.

• It makes the process more confusing.

• It reduces the number of candidates.

How does past hiring data influence current hiring decisions?

• It helps in predicting future hiring success.

• It has no influence at all.

• It complicates the decision-making process.

• It makes the process slower.

What is the challenge with candidates who fall on the boundary between hiring and not hiring?

• They are ignored in the decision-making process.

• They require careful consideration due to their position.

• They are always rejected.

• They are always hired.

What is a potential solution for dealing with confusing points in hiring decisions?

• Reject them immediately.

• Gather more data to make a better decision.

• Ignore them completely.

• Hire them without consideration.