Book Image

Machine Learning Using TensorFlow Cookbook

By : Luca Massaron, Alexia Audevart, Konrad Banachewicz
Book Image

Machine Learning Using TensorFlow Cookbook

By: Luca Massaron, Alexia Audevart, Konrad Banachewicz

Overview of this book

The independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data. Dive into recipes on training models, model evaluation, sentiment analysis, regression analysis, artificial neural networks, and deep learning - each using Google’s machine learning library, TensorFlow. This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data sources. You’ll discover real-world implementations of Keras and TensorFlow and learn how to use estimators to train linear models and boosted trees, both for classification and regression. Explore the practical applications of a variety of deep learning architectures, such as recurrent neural networks and Transformers, and see how they can be used to solve computer vision and natural language processing (NLP) problems. With the help of this book, you will be proficient in using TensorFlow, understand deep learning from the basics, and be able to implement machine learning algorithms in real-world scenarios.
Table of Contents (15 chapters)
5
Boosted Trees
11
Reinforcement Learning with TensorFlow and TF-Agents
13
Other Books You May Enjoy
14
Index

Visualizing Graphs in TensorBoard

Monitoring and troubleshooting machine learning algorithms can be a daunting task, especially if you have to wait a long time for the training to complete before you know the results. To work around this, TensorFlow includes a computational graph visualization tool called TensorBoard. With TensorBoard, we can visualize graphs and important values (loss, accuracy, batch training time, and so on) even during training.

Getting ready

To illustrate the various ways we can use TensorBoard, we will reimplement the MNIST model from The Introductory CNN Model recipe in Chapter 8Convolutional Neural Networks. Then, we'll add the TensorBoard callback and fit the model. We will show how to monitor numerical values, histograms of sets of values, how to create an image in TensorBoard, and how to visualize TensorFlow models.

How to do it...

  1. First, we'll load the libraries necessary for the script: ...