What's the difference between a basic and complex learning algorithm?

A basic algorithm has a set amount of choices to optimize for, while a complex algorithm is given the freedom to find its own model

A basic algorithm cannot use computer vision, while a complex algorithm can

A basic algorithm can handle simple inputs like numbers, while a complex algorithm can handle complex inputs like pictures

A basic algorithm cannot process more than $5$ steps in a function, while a complex algorithm can process up to $15$

When building a predictive model, what is the goal of the develop phase?

To get the model to accept new inputs, train, and repeat training until it finds a better curve

To plug in $40\%$ of your dataset, testing the model's accuracy

To specify the type of algorithm the model should use and make sure the data is cleaned$/$formatted

To get the model's error function below an acceptable percentage