> ## Documentation Index
> Fetch the complete documentation index at: https://aegean.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Statistical Learning Theory

> The learning problem, regression, gradient descent, and classification.

<CardGroup cols={2}>
  <Card title="The Learning Problem" icon="play" href="https://www.youtube.com/watch?v=Qw0Bdsa_3Yg">
    The Vapnik block diagram
  </Card>

  <Card title="Linear Regression (Part 1)" icon="play" href="https://www.youtube.com/watch?v=oLP7v-jCGxM">
    Extracting non-linear patterns with linear models
  </Card>

  <Card title="Linear Regression (Part 2)" icon="play" href="https://www.youtube.com/watch?v=86-gL8Dhhj0">
    Continuation of regression fundamentals
  </Card>

  <Card title="Gradient Descent" icon="play" href="https://www.youtube.com/watch?v=eWw5NPSxaa8">
    Optimizing with iterative methods
  </Card>

  <Card title="Entropy" icon="play" href="https://www.youtube.com/watch?v=V3FoNyppPl8">
    Information theory principles
  </Card>

  <Card title="Maximum Likelihood Estimation" icon="play" href="https://www.youtube.com/watch?v=CYxadbxMZno">
    The workhorse of statistical modeling
  </Card>

  <Card title="Binary Classification" icon="play" href="https://www.youtube.com/watch?v=eQ6UE968Xe4">
    Classification and decision boundaries
  </Card>

  <Card title="Logistic Regression" icon="play" href="https://www.youtube.com/watch?v=eFgkZKhNUdM">
    Binary classification with the logistic model
  </Card>
</CardGroup>

***

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