Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By : Nick McClure
Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By: Nick McClure

Overview of this book

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
Table of Contents (13 chapters)

Clustering using k-means

TensorFlow can also be used to implement iterative clustering algorithms, such as k-means. In this recipe, we show an example of using k-means on the iris dataset.

Getting ready

Almost all of the machine learning models we have explored in this book have been supervised models. TensorFlow is ideal for these types of problems. But, we can also implement unsupervised models if we wish. As an example, this recipe will implement k-means clustering.

The dataset we will implement clustering on is the iris dataset. One of the reasons this is a good dataset is because we already know there are three different targets (three types of iris flowers). This gives us a leg up on knowing that we are looking for three...