Book

Recurrent Neural Networks with Python Quick Start Guide

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 the 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.

Offered byPackt Logo

Difficulty Level

Intermediate

Completion Time

4h4m

Language

English

About Book

Who Is This Book For?

This book is for Machine Learning engineers and data scientists who want to learn about Recurrent Neural Network models with practical use-cases. Exposure to Python programming is required. Previous experience with TensorFlow will be helpful, but not mandatory.

Book content

chapters 4h4m total length

Introducing Recurrent Neural Networks

Building Your First RNN with TensorFlow

Generating Your Own Book Chapter

Creating a Spanish-to-English Translator

Build Your Personal Assistant

Improve Your RNN Performance

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