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    "https://www.youtube.com/watch?v=aircAruvnKk"
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{
  "videoId": "aircAruvnKk",
  "url": "https://www.youtube.com/watch?v=aircAruvnKk",
  "title": "But what is a neural network? | Deep learning chapter 1",
  "channelName": "3Blue1Brown",
  "channelUrl": "https://www.youtube.com/@3blue1brown",
  "durationSeconds": 1106,
  "language": {
    "code": "en",
    "name": "English",
    "isAutoGenerated": false
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  "languageMatched": true,
  "text": "This is a 3. It's sloppily written and rendered at an extremely low resolution of 28x28 pixels, but your brain has no trouble recognizing it as a 3. And I want you to take a moment to appreciate how crazy it is that brains can do this so effortlessly. I mean, this, this and this are also recognizable as 3s, even though the specific values of each pixel is very different from one image to the next. The particular light-sensitive cells in your eye that are firing when you see this 3 are very different from the ones firing when you see this 3. But something in that crazy-smart visual cortex of yours resolves these as representing the same idea, while at the same time recognizing other images as their own distinct ideas. But if I told you, hey, sit down and write for me a program that takes in…",
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      "start": 4,
      "end": 13.72,
      "text": "This is a 3. It's sloppily written and rendered at an extremely low resolution of 28x28 pixels, but your brain has no trouble recognizing it as a 3."
    },
    {
      "start": 14,
      "end": 18.96,
      "text": "And I want you to take a moment to appreciate how crazy it is that brains can do this so effortlessly."
    },
    {
      "start": 19,
      "end": 28.32,
      "text": "I mean, this, this and this are also recognizable as 3s, even though the specific values of each pixel is very different from one image to the next."
    },
    {
      "start": 28,
      "end": 36.94,
      "text": "The particular light-sensitive cells in your eye that are firing when you see this 3 are very different from the ones firing when you see this 3."
    },
    {
      "start": 37,
      "end": 48.34,
      "text": "But something in that crazy-smart visual cortex of yours resolves these as representing the same idea, while at the same time recognizing other images as their own distinct ideas."
    },
    {
      "start": 49,
      "end": 59.135,
      "text": "But if I told you, hey, sit down and write for me a program that takes in a grid of 28x28 pixels like this and outputs a single number between 0 and 10,"
    },
    {
      "start": 59,
      "end": 66.18,
      "text": "telling you what it thinks the digit is, well the task goes from comically trivial to dauntingly difficult."
    },
    {
      "start": 67,
      "end": 74.64,
      "text": "Unless you've been living under a rock, I think I hardly need to motivate the relevance and importance of machine learning and neural networks to the present and to the future."
    },
    {
      "start": 75,
      "end": 84.46,
      "text": "But what I want to do here is show you what a neural network actually is, assuming no background, and to help visualize what it's doing, not as a buzzword but as a piece of math."
    },
    {
      "start": 85,
      "end": 94.34,
      "text": "My hope is that you come away feeling like the structure itself is motivated, and to feel like you know what it means when you read, or you hear about a neural network quote-unquote learning."
    },
    {
      "start": 95,
      "end": 100.26,
      "text": "This video is just going to be devoted to the structure component of that, and the following one is going to tackle learning."
    },
    {
      "start": 100,
      "end": 106.04,
      "text": "What we're going to do is put together a neural network that can learn to recognize handwritten digits."
    }
  ],
  "chapters": [
    {
      "title": "Chapter 1: Introduction example",
      "start": 0
    },
    {
      "title": "Chapter 2: Series preview",
      "start": 67
    },
    {
      "title": "Chapter 3: What are neurons?",
      "start": 162
    },
    {
      "title": "Chapter 4: Introducing layers",
      "start": 215
    },
    {
      "title": "Chapter 5: Why layers?",
      "start": 331
    },
    {
      "title": "Chapter 6: Edge detection example",
      "start": 518
    },
    {
      "title": "Chapter 7: Counting weights and biases",
      "start": 694
    },
    {
      "title": "Chapter 8: How learning relates",
      "start": 750
    },
    {
      "title": "Chapter 9: Notation and linear algebra",
      "start": 806
    },
    {
      "title": "Chapter 10: Recap",
      "start": 917
    },
    {
      "title": "Chapter 11: Some final words",
      "start": 987
    },
    {
      "title": "Chapter 12: ReLU vs Sigmoid",
      "start": 1023
    }
  ],
  "scrapedAt": "2026-10-21T06:31:39.660Z"
}