##A simple Perceptron Learning Algorithm example. ###The file target.py generates n random points, where n is the user input. ###The file pla.py uses the PLA to determine a hypothesis. -Run as
-$ python pla.py
- The graph shows target function in yellow and the hypothesis in blue
- Notice how close both get as the number of points increase
- The following graph shows the same for 100 points as input
![My image] (100pts.png)
###Uses Python 2.7 with numpy, matplotlib