Original subtitles

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Hello and welcome back to the course on computer vision in today's tutorial We'll talk about the plan

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of attack.

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So what we will learn in the section about Ganns will first talk about the idea behind Janz and who

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came up with the idea and why they're generally even necessary in the world why the world needed them

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and how they have helped in the space of neural networks and computer vision progressed forward what

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purpose they serve.

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I think this will be a very important tutorial to lay the foundation of why we're going to be doing

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what we're doing in the section why it's important to learn about the guns.

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They all talk about how guns actually work.

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We'll get into the detail into the nitty gritty of Gannes and we'll actually look at three steps.

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This was a very long tutorial so I've broken down into three tutorials to represent the three steps

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that we take.

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So those are just three iterations of the training process which we'll look at in detail and watch our

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network grow is going to be very exciting to observe.

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But also keep in mind that these are just three steps out of the hundreds and thousands that actually

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happened during the training so you can imagine how you know what a small portion of the trained person

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we're going to be looking at.

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But at the same time just those three steps they will help us lay that intuition foundation.

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So when you get to the practical tutorials coding of online you will know exactly what is going on and

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exactly what's happening.

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Also we'll talk about applications all fudge of the guns and how they are changing the world how they

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are applied in so many different spaces and hopefully this tutorial will inspire you to call up your

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own applications and see how you can use Ganns in either your work or your hobbies or maybe your side

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projects that you might be working on a radio or might start after this course and this is quite a technical

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section.

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So Ari we have included some annexes to the Course to the bottom artificial neural networks and convolutional

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neural networks.

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Make sure to check them out and you will need them especially in this section because we'll be talking

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about things like back propagation and grey.

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We won't be actually talking a lot about backwardation gradient descent but they will be underpinning

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concepts in the process of training a neural network.

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So if you're not familiar aware of those concepts and highly encourage you to check out the annexes

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for the course before proceeding with the section because it will be helpful knowledge for you to really

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soak in the concepts that we're going to be talking about in the upcoming tutorials.

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And on that note I can't wait to get started with the first tutorial in this section and I'll look for

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it there.

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And until next time enjoy computer vision.