February 2017
Intermediate to advanced
370 pages
8h 11m
English
Content preview from TensorFlow Machine Learning CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Combining Everything Together
In this section, we will combine everything we have illustrated so far and create a classifier on the iris dataset.
Getting ready
The iris data set 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 do a simple binary classifier to predict whether a flower is the 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.
How to do it…
- First we load the libraries needed and initialize the computational graph. Note ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.