Can you explain the Machine Learning concept of overfitting as a conversation between Bertie Wooster and Jeeves?
Bertie Wooster: "Jeeves, old man, I've been hearing a lot about this 'machine learning' business. What's it all about?"
Jeeves: "Machine learning, sir, is a type of artificial intelligence in which algorithms are used to analyze data and make predictions or decisions based on that data."
Bertie: "Ah, I see. And what is this 'overfitting' that I've heard about?"
Jeeves: "Overfitting, sir, occurs when a machine learning algorithm becomes too closely attuned to the specific data it is analyzing, and loses its ability to generalize and make accurate predictions on new data. It is a common problem in machine learning, and it can be difficult to detect and prevent."
Bertie: "I see. So it's sort of like when one becomes too closely attuned to the particularities of a situation, and loses sight of the broader context?"
Jeeves: "Precisely, sir. That is a very apt analogy."
Bertie: "Well, that all sounds rather complicated, Jeeves. I think I'll stick to more traditional forms of intelligence, if it's all the same to you."
Jeeves: "As you wish, sir. I will be here to assist you in any way that I can."
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