Deep Learning - Deep Neural Network for Beginners Using Python - Problem with Linear Solutions

The video tutorial introduces the concept of a linear solution in machine learning, highlighting its foundational role. It discusses the limitations of linear solutions, particularly in scenarios like hiring an employee based on test scores and academic records. The tutorial emphasizes the need to modify training data to achieve better outcomes and concludes by encouraging viewers to think about alternative solutions.

What is a linear solution in the context of machine learning?

• A way to categorize employees

• A technique to modify data

• A method to draw random lines

• A foundational concept involving a straight line

Why might a linear solution be problematic when hiring an employee?

• It only considers academic records

• It may incorrectly categorize candidates with mixed records

• It always results in hiring the best candidate

• It ignores test scores

What should be done if a linear solution fails to provide accurate results?

• Continue using the same data

• Hire all candidates

• Modify the training data

• Ignore the problem

What is the main takeaway regarding the use of linear solutions?

• They are always the best choice

• They are foundational but have limitations

• They solve all problems

• They should be avoided

What is suggested when linear solutions do not work in most cases?

• To keep using them regardless

• To think about alternative solutions

• To hire based on intuition

• To abandon machine learning