This question is from a psychology lecture (Learning, Memory & Cognition, PSY2204) about the use of machine learning, AI, automation and bionics. Future of psychology

There are three broad types of machine learning - supervised learning, unsupervised learning, and reinforcement learning. Helen possesses a large database of love letters and would like to use machine learning to help her understand if there are any interesting patterns of language use present within the letters. Charlie would like to use machine learning to help him more efficiently detect tumours in medical images taken from cancer patients. Julia would like to develop an algorithm that will be highly proficient at playing the computer game Fortnite so that she can use the program as a training partner so that she can defeat her 12-year old daughter at the game who is always telling her to 'git gud'. Which type of machine learning is best suited for Helen's purpose? [1 point]. Which type of machine learning is best suited for Charlie's purpose? [1 point] And which type of machine learning is best suited for Julia's purpose? [1 point] Frank was in a car accident and suffered very bad injuries. Frank became paralysed from the waist down and was required to have his right arm amputated just above the elbow joint. For a prosthetic device for Frank's right arm would you recommend 'brain gate' technology or 'targeted muscle reinnervation' technology to work with the prosthesis? [1 point]. Explain your answer [2 points]