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BP neural network learning machine demonstration
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Application background Neural network is constructed by simulating human's neuron activity. Its basic unit is called "neuron", when the input is greater than a certain value, the neuron is excited, and the output is not responsive. And this input comes from all other neurons. The neuron's response function has a variety of (need to meet the micro, such a simple function can be fitted to any nonlinear function), select the SIGMOD function. The key of BP neural network is to deduce the formula of weight and threshold value.The basic idea of BP: the positive propagation of the signal is the error of the back propagation:- forward transmission: the input sample is passed from the input layer to the output layer. - back propagation: input error in some form through the hidden layer to the input layer by layer back propagation, and the error is apportioned to all the units of each layer, so as to obtain the error signal of the layers of units as
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Python to do with the Sudoku game
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Application background The design of Sudoku game, generate Sudoku, and input to determine whether the results of the establishment. With Python language, the more compact and concise. Can be used as a big problem for beginners python. Key Technology The project is decomposed into two parts, one is the generation of Sudoku; the second is to provide the game interface provides the results of the user's input function and check the result is correct.
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