TensorFlow Machine Learning Cookbook - Second Edition

How to do it...

We proceed with the recipe as follows:

1. First, we load the necessary libraries and initialize a graph, as follows:

import matplotlib.pyplot as plt 
import numpy as np 
import tensorflow as tf 
from sklearn import datasets 
sess = tf.Session()

2. Now, we load the data. This time, each element of x data will be a list of three values instead of one. Use the following code:

iris = datasets.load_iris() 
x_vals = np.array([[x[1], x[2], x[3]] for x in iris.data]) 
y_vals = np.array([y[0] for y in iris.data]) 

3. Next, we declare the batch size, placeholders, variables, and model output. The only difference here is that we change the size specifications of the x data placeholder to take three values instead of one, as follows:

batch_size ...