Book Image

Deep Learning with TensorFlow - Second Edition

By : Giancarlo Zaccone, Md. Rezaul Karim
Book Image

Deep Learning with TensorFlow - Second Edition

By: Giancarlo Zaccone, Md. Rezaul Karim

Overview of this book

Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you’ll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.
Table of Contents (15 chapters)
Deep Learning with TensorFlow - Second Edition
Contributors
Preface
Other Books You May Enjoy
Index

tf.estimator


tf.estimator is a high-level TensorFlow API for creating and training models by encapsulating the functionalities for training, evaluating, predicting and exporting. TensorFlow recently re-branded and released the TF Learn package within TensorFlow under a new name, TF Estimator, probably to avoid confusion with the TFLearn package from tflearn.org.

tf.estimator allows developers to easily extend the package and implement new ML algorithms by using the existing modular components and TensorFlow's low-level APIs, which serve as the building blocks of ML algorithms. Some examples of these building blocks are evaluation metrics, layers, losses, and optimizers.

The main features provided by tf.estimator are described in the next sections.

Estimators

An estimator is a rule that calculates an estimate of a given quantity. Estimators are used to train and evaluate TensorFlow models. Each estimator is an implementation of a particular type of ML algorithm. They currently support regression...