TensorFlow 1.x Deep Learning Cookbook

How to do it...

Here is how we proceed with the single layer perceptron:

1. Import the modules needed:

import tensorflow as tf 
import numpy as np 
 

2. Define the hyperparameters to be used:

# Hyper parameters 
eta = 0.4  # learning rate parameter 
epsilon = 1e-03 # minimum accepted error 
max_epochs = 100 # Maximum Epochs 
 

3. Define the threshold function:

# Threshold Activation function 
def threshold (x): 
    cond = tf.less(x, tf.zeros(tf.shape(x), dtype = x.dtype)) 
    out = tf.where(cond, tf.zeros(tf.shape(x)), tf.ones(tf.shape(x))) 
    return out 

4. Specify the training data. In this example, we take a three input neuron (A,B,C) and train it to learn the logic AB + BC:

# Training Data Y = AB + BC, sum of two linear functions. T, F = 1., 0. X_in = [ [T, T, ...