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Your paper on viral propagation was very insightful.

In particular, we'll talk about the back propagation algorithm.

Or any evidence of fracture propagation within the tectonic plates.

My story is actually not about plant propagation, but about pollen itself.

We were studying wave propagation, and I couldn't understand this one problem, this one equation.

Next, in order to compute the derivatives, we're going to use an algorithm called back propagation.

So that's the back propagation algorithm and how you compute derivatives of your cost function for a neural network.

The fund was, of course, for the propagation and spread of the red heads as well as for their maintenance.

They will be told, This (torment) is the result of your unreasonable happiness on the earth and of your propagation of falsehood.

This is just the theorem of total probability or forward propagation rule applied to this case over here, so nothing really new.

The first thing we do is we apply forward propagation in order to compute whether a hypotheses actually outputs given the input.

Let's take everything and put it all together to talk about how to implement back propagation to compute derivatives with respect to your parameters.

So this is our vectorized implementation of forward propagation and it allows us to compute the activation values for all of the neurons in our neural network.

Next we apply 2 more steps of this four and propagation to compute a(3) and a(4) which is also the upwards of a hypotheses h of x.

He who has assigned (the propagation) of the Qur'an to you will bring you back to the destination. Say My Lord knows who has come to guidance, and who is clearly in error.

launch and propagation of a Charter for Compassion, crafted by a group of inspirational thinkers from the three Abrahamic traditions of Judaism, Christianity and Islam, and based on the fundamental principle of the Golden Rule.

We'll fix this detail later about the regularization term, but so by performing back propagation and computing these delta terms, you can, you know, pretty quickly compute these partial derivative terms for all of your parameters.

The intuition of the back propagation algorithm is that for each note we're going to compute the term delta superscript I subscript j that's going to somehow represent the error of note j in the layer l.

It actually turns out, though, even though we've only known of long range propagation for a few decades, the whales clearly have evolved, over tens of millions of years, a way to exploit this amazing property of the ocean.

So the first thing we're going to do is set a1 which is the activations of the input layer, set that to be equal to xi is the inputs for our i training example, and then we're going to perform forward propagation to compute the activations for

And then we're going to use the back propagation algorithm to compute delta L minus 1, delta L minus 2, and so on down to delta 2 and once again there is now delta 1 because we don't associate an error term with the input layer.

But both in the programming assignments write out and later in this video, we'll give you a summary of this so we can have all the pieces of the algorithm together so that you know exactly what you need to implement if you want to implement back propagation to compute the derivatives of your neural network's cost function with respect to those parameters.

The name back propagation comes from the fact that we start by computing the delta term for the output layer and then we go back a layer and compute the delta terms for the third hidden layer and then we go back another step to compute delta 2 and so, we're sort of back propagating the errors from the output layer to layer 3 to their to hence the name back complication.