Deep Learning - Deep Neural Network for Beginners Using Python - Problem to Solve Part 1

The video tutorial discusses using deep neural networks for problem-solving, specifically in hiring decisions. It explains how to evaluate potential employees based on their academic qualifications and test scores, normalized on a scale of 10. The tutorial compares two candidates, highlighting the importance of higher scores in both academics and tests for hiring decisions. It concludes with a thought-provoking scenario involving a candidate with average scores, encouraging viewers to consider their decision-making criteria.

What are the two main factors considered in the hiring decision process discussed in the video?

• Experience and test scores

• Leadership skills and test scores

• Academic qualifications and test scores

• Communication skills and academic qualifications

Which candidate is deemed more suitable for hiring based on their scores?

• The candidate with 7 marks in test and 9 marks in academics

• The candidate with 3 marks in test and 2 marks in academics

• The candidate with 6 marks in test and 6 marks in academics

• The candidate with 5 marks in test and 5 marks in academics

Why is the candidate with lower scores in both test and academics not considered for hiring?

• Because they have lower scores in both test and academics

• Because they have higher scores in other areas

• Because they have more experience

• Because they have a better resume

What is the dilemma presented with the new candidate having equal scores in test and academics?

• Whether to consider only test scores

• Whether to hire based on equal scores or not

• Whether to hire based on experience

• Whether to ignore academic scores

What should be considered when evaluating a candidate with equal scores in both test and academics?

• Their potential for growth

• Their communication skills

• Their leadership skills

• Their equal scores in both areas