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Create our own target function f and data set D and see how the perceptron learning algorithm works. Take d = 2 so you can visualize the problem, and choose a random line in the plane as your target function, where one side of the line maps to +1 and the other maps to -1. Choose the inputs x, of the data set as random points in the plane, and evaluate the target function on each xn to get the corresponding output yn Now, generate a data set of size 20. Try the perceptron learning algorithm on your data set and see how long it takes to converge and how well the final hypothesis g matches your target f.

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Create a class hand in its own module. one object of class hand represents a hand of cards and so one object stores a number of card objects. for this assignment you will submit three separate modules, one with the definition of class card, one with the definition of class hand and one with the main application that thoroughly tests class hand. class hand must contain the following four methods: 1) , numcardsinhand) takes an integer as parameter and initializes a hand object with numcardsinhand card objects inside it. these card objects are generated randomly. for simplicity, assume an infinite number of decks of cards.2) bjvalue(self) returns the blackjack value for the whole hand of cards3) ) returns a string containing all the cards in the hand4) hitme(self) adds one randomly generated card to the handcreate a main program in its own module that thoroughly tests class hand. you will have three modules/files to upload to your etudes assignment submission: card. py, hand. py and the module that contains your main program. two alternatives for extra credit - you cannot get credit for both! (+1 point): after you have thoroughly tested the class hand and all of its methods, add code to your main program that stores one hand object as a pickle file and reads it back into a new hand object. you are only eligible for this extra credit if class hand has all four of the methods above working. or(+2 points): after you have thoroughly tested the class hand and all of its methods, add code to your main program that stores one hand object as a text file on the disk and reads it back into a new hand object. you are only eligible for this extra credit if class hand has all four of the methods above working. notes: -start by making any and all modifications suggested by my comments to your previous submission of class card from assignment #6 "a robust card object"-once your class card is tested and working well, you will not make any further modifications to it for the purposes of class hand.-you can keep the test code for class card intact. if it is indented inside an if __name__ == "__main__", then it will not be executed when your main program's module imports it.-to save time, write and test one method for class hand at a time.-under no circumstances are you to attempt the extra credit until you are completely finished with writing and testing all the methods in class hand.
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Create our own target function f and data set D and see how the perceptron learning algorithm works....

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