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 by
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.
Recurrent Neural Networks with Python Quick Start Guide
- About Book
- Who Is This Book For?
- Book Content
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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