TensorFlow Machine Learning Cookbook - Second Edition

How to do it...

Here is how the regression example works:

1. We start by loading the numpy and tensorflow numerical Python packages:

import numpy as np 
import tensorflow as tf 

2. Now, we start a graph session:

sess = tf.Session() 

3. Next, we create the data, placeholders, and the A variable:

x_vals = np.random.normal(1, 0.1, 100) 
y_vals = np.repeat(10., 100) 
x_data = tf.placeholder(shape=[1], dtype=tf.float32) 
y_target = tf.placeholder(shape=[1], dtype=tf.float32) 
A = tf.Variable(tf.random_normal(shape=[1])) 

4. We add the multiplication operation to our graph:

my_output = tf.mul(x_data, A) 

5. Next, we add our L2 Loss function between the multiplication output and the target data:

loss = tf.square(my_output - y_target)

6. Now, we have to declare ...