Deep Learning - Crash Course 2023 - Perceptron

The video introduces the perceptron model, highlighting its ability to handle real number inputs while maintaining a binary output for classification. It discusses the model's linear data separation and the flexibility to adjust parameters like weight and slope. The unique loss function of the perceptron is explained, along with a principled approach to updating parameters. The video concludes with a brief mention of model evaluation using accuracy.

What is the nature of the loss function in the perceptron model?

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How will the model's accuracy be evaluated in the perceptron model?

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