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75 probability is for the dropout zone. The function conv2d is called from conv_net which is basically the main function which does the work of navigating through the input image. The first dimension being the batch size which will be specified later. What the convolution does to come up with the 32 or 64 outputs is left to the reader to investigate. Let’s finish by going over the following 4 lines the entire code base is on the code site. The softmax_cross_entropy_with_logits takes the output of the prediction tensor which has a size of 10 and the actual value of the training sample which is also a tensor of size 10 (no of classes) and comes out with a probability value whose mean is then calculated for digits 0,1,2,3,4,5,6,7,8,9 separately by minimizing the error in the entropy for all dimensions which are the 10 dimensions of the scores for each 0, 1, 2, 3,4,5,6,7,8,9.

What the convolution does to come up with the 32 or 64 outputs is left to the reader to investigate. Let’s finish by going over the following 4 lines the entire code base is on the code site. The softmax_cross_entropy_with_logits takes the output of the prediction tensor which has a size of 10 and the actual value of the training sample which is also a tensor of size 10 (no of classes) and comes out with a probability value whose mean is then calculated for digits 0,1,2,3,4,5,6,7,8,9 separately by minimizing the error in the entropy for all dimensions which are the 10 dimensions of the scores for each 0, 1, 2, 3,4,5,6,7,8,9.

Direction and magnitude, the change in direction in 1 dimension is signified by change in sign of the magnitude number. There is a python simulation of gradient descent in the additional materials folder on Google cloud storage. There are other variations of the Gradient descent algorithm available one most popular is Stochastic gradient descent where we calculate the minima at each point using a shuffled set of data points there by reducing the risk of getting stuck in a local minima. run command executes the Tensor flow directed graph, and the cost node is passed in along with the training values.

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mACHINE lEARNING eXPERIMENTS by Sanshodhana LP


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