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Using airSlate SignNow’s eSignature any business can speed up signature workflows and eSign in real-time, delivering a better experience to customers and employees. send lots placeholder in a few simple steps. Our mobile-first apps make working on the go possible, even while offline! Sign documents from anywhere in the world and close deals faster.
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Send lots placeholder
hello everyone will come back to the tensorflow tutorial series this time we'll talk about the placeholder actually the placeholder is just similar to the variable but every time when you use the placeholder you will do the fitting process that to say for every time the placeholder did the value that they hold is a different value for example for example I would define the placeholder first they an to fit the placeholder later when I wanna when I was doing training so imports tensors Louis here and just inputs you define the input 1 input 1x is equal to you have that placeholder here that a lot 32 as I mentioned before the default type of tensorflow is what 32 because if you run other types like int 32 of floats 64 floats 16 there will be some errors showing in your program dad's just make sure because the most of the time that in the flow are using the float 32 so you just use floats to the two everywhere in your tensorflow coats floor define another one input 2 is just another placeholder in this example we don't have any shape for the placeholder that's in your example you could define the shape if for example it's a two column two roll shape for the input one or tube color and two two rows two colored shape for the placeholder one but in this example we just ignore this shape and the output is just like multiply operation just input one pumps in co2 when we're going to pass the value into the placeholder is once we define after we define the session so with the TF dots session we have defined a session so now we can use sessions around to run this output operation I run these outputs we must give the outputs Q values one for input one 1.42 because the output constant the input 1 input 2 which is a placeholder so we should pass the value for this two by using feet dictionary equals 2 this one is just like Python dictionary so you have to define the key input one for the as the key for input 1 and the value for input 1 so for example 7 and the value the key for input 2 and the value for input 2 maybe two so they were the opacity of 7 inches a placeholder one and pass the value 2 into the placeholder - and do the altitude operation for you and then we just print this result for this with the output down that is 14 right 2 times 7 is 14 so this is for today's tutorial it's fairly easy one but it's really useful when you do the placeholder later on other example so make sure you understand what is placeholder and the ball is different between placeholder day and still variable so next time we're going to talk about the activation function in neural network it's not only intensive law it's also in the new network it's very important parts for understanding that so hope you like that and please subscribe for more updates of tensor flow or other machine learning problem so see you next time bye
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