Linear Limitations
Learn to identify the limitations of single layer perceptron models, especially their inability to classify data with nonlinear decision boundaries. This lesson uses TensorFlow to illustrate how these models successfully classify points separated by linear boundaries but fail with nonlinear shapes like circles, setting the stage for deeper neural network architectures.
We'll cover the following...
We'll cover the following...
Chapter Goals:
- Understand the limitations of a single layer perceptron model
A. Linear decision boundary
The input data we've been using to train and evaluate the single layer perceptron model has been pairs of (x, y) points with labels indicating whether the point is above (labeled 1) or below (labeled 0) the y = x line. ...