What types of Machine Learning, if any, best describe the following three scenarios: (i) A coin classification system is created for a vending machine. The developers obtain exact coin specifications from the U. S. Mint and derive a statistical model of the size, weight, and denomination, which the vending machine then uses to classify coins. (ii) Instead of calling the U. S. Mint to obtain coin information, an algorithm is presented with a large set of labeled coins. The algorithm uses this data to infer decision boundaries which the vending machine then uses to classify its coins. (iii) A computer develops a strategy for playing Tic-Tac-Toe by playing repeatedly and adjusting its strategy by penalizing moves that eventually lead to losing.

i. No learning;

ii. Supervised learning;

iii. Reinforcement learning

Explanation:

Machine learning is an application of artificial intelligence (AI) which gives systems ability to learn automatically learn without the systems being programmed. Machine learning are used eto make vital decisions in the forecasting of energy load, trading of stock, medical diagnosis, etc.

The types of Machine Learning that describe the scenarios are:

i) No learning - This is because the machine is not learning anything from the data as the algorithms is used in the identification of coins.

ii) Supervised learning –This s due to the fact that labeled coins is being gotten by the machine which is a sort of training given to the machine.

iii. Reinforcement learning – This is because the computer system is only learning from rewards it gets whenever a move is made by it.

i think the answer is b.

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