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Deep Learning: Recurrent Neural Networks with Python
Deep Learning: Recurrent Neural Networks with Python

Deep Learning: Recurrent Neural Networks with Python: Master, train, and build recurrent neural networks with Python

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Profile Icon AI Sciences
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$59.99
Video Feb 2021 15hrs 35mins 1st Edition
Video
$59.99
Video + Subscription
$24.99 Monthly
Arrow left icon
Profile Icon AI Sciences
Arrow right icon
$59.99
Video Feb 2021 15hrs 35mins 1st Edition
Video
$59.99
Video + Subscription
$24.99 Monthly
Video
$59.99
Video + Subscription
$24.99 Monthly

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Key benefits

  • Understand and apply fundamentals of recurrent neural networks
  • Implement RNNs and related architectures on real-world datasets
  • Train RNNs for real-world applications—automatic book writer and stock price prediction

Description

With the exponential growth of user-generated data, there is a strong need to move beyond standard neural networks in order to perform tasks such as classification and prediction. Here, architectures such as RNNs, Gated Recurrent Units (GRUs), and Long Short Term Memory (LSTM) are the go-to options. Hence, for any deep learning engineer, mastering RNNs is a top priority. This course begins with the basics and will gradually equip you with not only the theoretical know-how but also the practical skills required to successfully build, train, and implement RNNs. This course contains several exercises on topics such as gradient descents in RNNs, GRUs, LSTM, and so on. This course also introduces you to implementing RNNs using TensorFlow. The course culminates in two exciting and realistic projects: creating an automatic book writer and a stock price prediction application. By the end of this course, you will be equipped with all the skills required to confidently use and implement RNNs in your applications. The code bundle for this course is available at https://github.com/AISCIENCES/mastering_recurrent_neural_networks

Who is this book for?

As this course begins with the basics, no prior knowledge in RNNs is required. However, prior experience in Python would be beneficial. Whether you are a beginner, a seasoned data scientist looking to get started with RNNs, business analysts, or if you simply want to implement RNNs in your projects, this course is for you.

What you will learn

  • Gain an overview of deep neural networks
  • Understand the fundamentals of RNN architectures
  • Train real-world datasets using different RNN architectures
  • Implement RNNs, LSTM, and GRUs through hands-on exercises
  • Create and compile RNN models in TensorFlow
  • Perform text classification using RNNs and TensorFlow

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Last updated date : Jul 02, 2026
Publication date : Feb 26, 2021
Length: 15hrs 35mins
Edition : 1st
Language : English
ISBN-13 : 9781801079167
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What do you get with a Packt Premium Subscription?

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Product feature icon Weekly additions on emerging tech and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon A monthly credit and 50% off any future digital purchases.

Product Details

Last updated date : Jul 02, 2026
Publication date : Feb 26, 2021
Length: 15hrs 35mins
Edition : 1st
Language : English
ISBN-13 : 9781801079167
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total $ 163.97
Deep Learning: Recurrent Neural Networks with Python
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Table of Contents

12 Chapters
Introduction Chevron down icon Chevron up icon
Applications of RNN Chevron down icon Chevron up icon
Deep Neural Network (DNN) Overview Chevron down icon Chevron up icon
RNN Architecture Chevron down icon Chevron up icon
Gradient Descent in RNN Chevron down icon Chevron up icon
RNN Implementation Chevron down icon Chevron up icon
Sentiment Classification Using RNN Chevron down icon Chevron up icon
Vanishing Gradients in RNN Chevron down icon Chevron up icon
TensorFlow Chevron down icon Chevron up icon
Project 1: Book Writer Chevron down icon Chevron up icon
Project 2: Stock Price Prediction Chevron down icon Chevron up icon
Further Reading and Resources Chevron down icon Chevron up icon
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