What's up creators? Welcome to the second episode of my new series, Vroid's AI. In this episode, I'll be talking about the forward propagation part of a neural network. If you haven't already, make sure to watch the first part of this series as it briefly covers the entire process of training and running a neural network. The forward propagation part of a neural network is the act of propagating the input values through the network to produce an output. Simply put, it's the neural network in function. I explained in the last episode how synapses or weights work, but quickly, here is an explanation again. Each synapse multiplies its own weight by its input and the result gets added to its output. So 1 times 0.7 is 0.7 and 1 times negative 0.2 is negative 0.2. So when you add 0.7 and negative 0.2, you get 0.5. I said in the last episode that this simple action stays the same in a large neural network. And while that is true, chances are that that didn't get across the whole point. So here's an example of how it works. In this example, you can see that the values are abstract. You get your inputs, you multiply them by the weights, and then you add those two values together to get your output. So 8 times 0.4 is 3.2, 3 times 1.8 is 5.4. When you add those together, you get 8.6 and that's the first neuron. So then you just repeat that with all the other neurons and that's the first hidden layer. So where to go from here? You just disable the first input layer and that first hidden layer becomes the input layer. Technically, when you're applying this, you don't really just disable the input layer. It stays the same, but for explanation purposes, this makes more sense. So after that, you just calculate second hidden layer and of course, remove the first hidden layer. And now you're done the last step which is where you're multiply the weights again and get the output. So that's the entire process. As you can see, there wasn't really anything different. It was just on a larger scale. I hope at this point you can understand the process of forward propagation. As always, if you think you have anything you could have explained better, make sure to leave it in the comments so I can take into consideration for upcoming or revised videos. Thanks for watching. If you enjoyed this video, make sure to leave a like and check out some of my other videos. If you haven't already, subscribe and enable notifications so you can know whenever I upload. See you in the next video.