QUESTION 1

(30 MARKS)

1.1 Can you describe the various steps and processes involved in the Machine

Learning life cycle when developing a predictive model for a complex real-world

scenario, without relying solely on code or programming language? (10)

1.2 How can one conceptualize and understand the impact of overfitting and

underfitting in a predictive model, and what are the strategies for avoiding these

problems when working on real-world applications, without relying solely on code

or programming language?

(10)

1.3 Can you explain the fundamental concepts and differences between regression

and classification in the field of Machine Learning, without using code or

programming language? How do these two techniques differ in terms of their

objectives, inputs, and outputs, and when is each appropriate to use in a real-world

scenario?

(10)