neuralnets.md

Bias Weight

Default input is 1 and some random weight value.

Perceptrons

Consist of Input, Output, and Weight

OR GATE Perceptron Neural Net

import codecademylib3_seaborn
from sklearn.linear_model import Perceptron
import matplotlib.pyplot as plt
import numpy as np
from itertools import product

data = [[0,0],[0,1],[1,0],[1,1]]
labels = [0,1,1,1]

plt.scatter([point[0] for point in data],[point[1] for point in data], c=labels)


classifier = Perceptron(max_iter = 40)
classifier.fit(data,labels)
print(classifier.score(data,labels))
x_values = np.linspace(0,1,100)
y_values = np.linspace(0,1,100)
point_grid = list(product(x_values,y_values))
distances = classifier.decision_function(point_grid)

abs_distances = [abs(pt) for pt in distances]
distances_matrix = np.reshape(abs_distances,(100,100))

plt.pcolormesh(x_values,y_values, distances_matrix)

plt.show()