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Building Your First RNN with TensorFlow

In this chapter, you will gain a hands-on experience of building a recurrent neural network (RNN). First, you will be introduced to the most widely used machine learning library—TensorFlow. From learning the basics to advancing into some fundamental techniques, you will obtain a reasonable understanding of how to apply this powerful library to your applications. Then, you will take on a fairly simple task of building an actual model. The process will show you how to prepare your data, train the network, and make predictions.

In summary, the topics of this chapter include the following:

What are you going to build?: Introduction of your task
Introduction to TensorFlow: Taking first steps into learning the TensorFlow framework
Coding the RNN: You will go through the process of writing your first neural network using TensorFlow. This...

Key benefits

Train and deploy Recurrent Neural Networks using the popular TensorFlow library

Apply long short-term memory units

Expand your skills in complex neural network and deep learning topics

Description

Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling. Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood. After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field.

What you will learn

Use TensorFlow to build RNN models

Use the correct RNN architecture for a particular machine learning task

Collect and clear the training data for your models

Use the correct Python libraries for any task during the building phase of your model

Optimize your model for higher accuracy

Identify the differences between multiple models and how you can substitute them

Learn the core deep learning fundamentals applicable to any machine learning model

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

Recurrent Neural Networks with Python Quick Start Guide

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Total € 91.97

Amazon Customer Nov 11, 2019

Worth the time and worth the read. Excellent writing. I learned a lot about exactly what I was looking for.Cliff

Amazon Verified review

PC Jun 29, 2020

Could go more into detail and cite papers.

CustomerAmz Dec 10, 2019

I was expecting more on the topic, the content covered can be easily found in any book on deep learning.Examples can also be found in general deep learning book.This book had to provide much in depth into the topic.Some references are given so I am giving one extra star to the book.

Tito Apr 19, 2020

Code and operations in this book is no longer supported. There is no errata or update for that in the website of packt. The other issue is that there are critical diagrams missing in the book. It says referring to the above diagram but there are none. If you want to take steps backward in your learning then go ahead buy this book.

Recurrent Neural Networks with Python Quick Start Guide: Sequential learning and language modeling with TensorFlow

What do you get with Print?

Recurrent Neural Networks with Python Quick Start Guide

Building Your First RNN with TensorFlow

What are you going to build?

Introduction to TensorFlow

Graph-based execution

Coding the recurrent neural network

Generating data

Summary

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Recurrent Neural Networks with Python Quick Start Guide: Sequential learning and language modeling with TensorFlow

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