Deep Learning and AI Superhero

Practical Exercises Chapter 1

Exercise 1: Implementing a Simple Perceptron

Task: Implement a perceptron for the AND logic gate. Train the perceptron using the Perceptron learning algorithm and test it on the same data.

Input 1	Input 2	Output
0	0	0
0	1	0
1	0	0
1	1	1

Solution:

import numpy as np

class Perceptron:

def __init__(self, learning_rate=0.01, n_iters=1000):

self.learning_rate = learning_rate

self.n_iters = n_iters

self.weights = None

self.bias = None

def fit(self, X, y):

n_samples, n_features = X.shape

self.weights = np.zeros(n_features)

self.bias = 0

for _ in range(self.n_iters):

for idx, x_i in enumerate(X):

linear_output = np.dot(x_i, self.weights) + self.bias

y_predicted = self.activation_function(linear_output)

# Update rule

update = self.learning_rate ...