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【機器學(xué)習(xí)】-Week6.1 Evaluating a Hypothesis
Once we have done some trouble shooting for errors in our predictions by...
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【機器學(xué)習(xí)】-Week5.6 Putting it TogetherFirst, pick a network architecture; choose the layout of your neural net...
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【機器學(xué)習(xí)】-Week5.5 Random InitializationInitializing all theta weights to zero does not work with neural network...
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【機器學(xué)習(xí)】-Week5.5 Gradient Checking
Gradient Checking Gradient checking will assure that our backpropagation...
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【機器學(xué)習(xí)】-Week5.4 Implementation Note: Unrolling Parameters
With neural networks, we are working with sets of matrices: In order to ...
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【機器學(xué)習(xí)】-Week5.3 Backpropagation IntuitionRecall that the cost function for a neural network is: If we consider si...
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【機器學(xué)習(xí)】-Week5.2 Backpropagation Algorithm （神經(jīng)網(wǎng)絡(luò)）Backpropagation Algorithm "Backpropagation" is neural-network terminolog...
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【機器學(xué)習(xí)】-Week5.1 Cost Function （神經(jīng)網(wǎng)絡(luò)）
Cost Function Let's first define a few variables that we will need to us...
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【機器學(xué)習(xí)】-Week4.5 Multiclass ClassificationMulticlass Classification To classify data into multiple classes, we let...