TensorFlow Complete Code

TensorFlow Complete Code

The iris data set is described in more detail in Working with Data Sources in Getting Started with TensorFlow. We will load this data, and do a simple binary classifier to predict whether a flower is a species Iris setosa or not. To be clear, this dataset has three classes of species, but we will only predict whether it 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. Combining Everything Together. TensorFlow Complete Code

Create a classifier on the iris dataset.

Getting ready

The iris data set is described in more detail in Working with Data Sources in Getting Started with TensorFlow. We will load this data, and do a simple binary classifier to predict whether a flower is a species Iris setosa or not. To be clear, this dataset has three classes of species, but we will only predict whether it 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.

Source: TensorFlow Machine Learning Cookbook

How to do it…

  1. 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 resulting line after:
import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets
import tensorflow as tf
sess = tf.Session()

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