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In this model I have built using Python, I explore using machine learning to predict whether a borrower will default on their unsecured loan, before they are issued the loan. This is model is applicable to the pre-screening process for lenders issuing unsecured loans. The application of machine learning allows lenders to derive more accurate insights about the probability of default for any individual than they would otherwise be able to using a simple system of Fico-score thresholds.
The Monty Hall problem is a classic thought experiment in probability. It derives its name from Monty Hall who was the host in the game show, "Lets Make A Deal". On the show, the contestant is presented with 3 curtains. The contestant is told that behind one of these curtains is a prize and the other curtains are empty. The contestant is than told to choose one curtain. After the contestant choses a curtain, the host reveals one of the two remaining curtains as empty. The contestant is then asked by the host whether they would like to switch curtains or not, before he reveals the curtain that has the prize. The simulation experiment in this case is to test which is the better option for the contestant to switch curtains or not switch curtains before the reveal.
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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