Combining everything together
In this section, we will combine everything we have illustrated so far and create a classifier for the iris dataset.
Getting ready
The iris dataset is described in more detail in the Working with data sources recipe in Chapter 1, Getting Started with TensorFlow. We will load this data and make a simple binary classifier to predict whether a flower is the species Iris setosa or not. To be clear, this dataset has three species, but we will only predict whether a flower is a single species, I. setosa or not, giving us a binary classifier. We will start by loading the libraries and data, then transform the target accordingly.
How to do it...
We proceed with the recipe as follows:
- First, we load the libraries needed and initialize the computational graph. Note that we also load
matplotlib
here, because we would like to plot the resultant line afterward:
import matplotlib.pyplot as plt import numpy as np from sklearn import datasets import tensorflow as tf sess =...