0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

R Deep Learning Cookbook

You're reading from R Deep Learning Cookbook Solve complex neural net problems with TensorFlow, H2O and MXNet

Product type Paperback

Published in Aug 2017

Publisher Packt

ISBN-13 9781787121089

Length 288 pages

Edition 1st Edition

Languages

R

Tools

H2O

Concepts

Deep Learning

Authors (2):

Achyutuni Sri Krishna Rao

PKS Prakash

View More author details

Table of Contents (11) Chapters

Preface

1. Getting Started FREE CHAPTER

2. Deep Learning with R

3. Convolution Neural Network

4. Data Representation Using Autoencoders

5. Generative Models in Deep Learning

6. Recurrent Neural Networks

7. Reinforcement Learning

8. Application of Deep Learning in Text Mining

9. Application of Deep Learning to Signal processing

10. Transfer Learning

Installing R with an IDE

Before we begin, let's install an IDE for R. For R the most popular IDEs are Rstudio and Jupyter. Rstudio is dedicated to R whereas Jupyter provide multi-language support including R. Jupyter also provides an interactive environment and allow you to combine code, text, and graphics into a single notebook.

Getting ready

R supports multiple operating systems such as Windows, macOS X, and Linux. The installation files for R can be downloaded from any one of the mirror sites at Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/. The CRAN is also a major repository for packages in R. The programming language R is available under both 32-bit and 64-bit architectures.

How to do it...

Of r-base-dev is also highly recommended as it has many inbuilt functions. It also enables the install.packages() command, which is used to compile and install new R packages directly from the CRAN using the R console. The default R console looks as follows:

Default R console

For programming purposes, an Integrated Development Environment (IDE) is recommended as it helps enhance productivity. One of the most popular open source IDEs for R is Rstudio. Rstudio also provides you with an Rstudio server, which facilitates a web-based environment to program in R. The interface for the Rstudio IDE is shown in the following screenshot:

Rstudio Integrated Development Environment for R

You have been reading a chapter from

R Deep Learning Cookbook

Published in: Aug 2017

Publisher: Packt

ISBN-13: 9781787121089

© 2017 Packt Publishing Limited All Rights Reserved

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at €18.99/month. Cancel anytime

Authors (2)

PKS Prakash

PKS Prakash

Dr. PKS Prakash is a data scientist and author. He has spent the last 12 years in developing many data science solutions in several practical areas in healthcare, manufacturing, pharmaceuticals, and e-commerce. He currently works as the data science manager at ZS Associates. He is the co-founder of Warwick Analytics, a spin-off from University of Warwick, UK. Prakash has published articles widely in research areas of operational research and management, soft computing tools, and advanced algorithms in leading journals such as IEEE-Trans, EJOR, and IJPR, among others. He has edited an article on Intelligent Approaches to Complex Systems and contributed to books such as Evolutionary Computing in Advanced Manufacturing published by WILEY and Algorithms and Data Structures using R and R Deep Learning Cookbook, published by PACKT.

See other products by PKS Prakash

Sri Krishna Rao

Sri Krishna Rao

Achyutuni Sri Krishna Rao is a Data Scientist, a Civil Engineer and an Author. He has spent last 4 years in developing many data science solutions to solve problems from leading companies in healthcare, pharmaceutical and manufacturing domain. He is working as Data Science Consultant at ZS Associates. Sri Krishnas background involves a masters in Enterprise Business Analytics and Machine Learning from National University of Singapore, Singapore. His other educational background involves a Bachelors from National Institute of Technology Warangal, India. Sri Krishna has published widely in research areas of civil engineering. He has contributed in a book titled Algorithms and Data Structures using R published by PACKT.

See other products by Sri Krishna Rao

Other recommended products

Related to this chapter

Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN's best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

Feb 2018 7h 16m

Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN's best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

Feb 2018 7h 16m

Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN's best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

Feb 2018 7h 16m

Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN's best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

Feb 2018 7h 16m

Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN's best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

Feb 2018 7h 16m

Practical Convolutional Neural Networks

Practical Convolutional Neural Networks

This book helps you master CNN, from the basics to the most advanced concepts in CNN such as GANs, instance classification and attention mechanism for vision models and more. You will implement advanced CNN models using complex image and video datasets. By the end of the book you will learn CNN's best practices to implement smart ConvNet models and apply them to solve complex deep learning problems.

Feb 2018 7h 16m

Advanced Deep Learning with R

Advanced Deep Learning with R

This book will help readers to apply deep learning algorithms in R using advanced examples. You will cover variants of neural network models such as ANN, CNN, RNN, LSTM, and more using expert techniques. Readers will make use of popular deep learning libraries such as Keras-R, Tensorflow-R, and more to implement AI models.

Dec 2019 11h 44m

Advanced Deep Learning with R

Advanced Deep Learning with R

This book will help readers to apply deep learning algorithms in R using advanced examples. You will cover variants of neural network models such as ANN, CNN, RNN, LSTM, and more using expert techniques. Readers will make use of popular deep learning libraries such as Keras-R, Tensorflow-R, and more to implement AI models.

Dec 2019 11h 44m

Advanced Deep Learning with R

Advanced Deep Learning with R

This book will help readers to apply deep learning algorithms in R using advanced examples. You will cover variants of neural network models such as ANN, CNN, RNN, LSTM, and more using expert techniques. Readers will make use of popular deep learning libraries such as Keras-R, Tensorflow-R, and more to implement AI models.

Dec 2019 11h 44m

Neural Network Programming with Tensorflow

Neural Network Programming with Tensorflow

If you're aware of the buzz surrounding the terms such as machine learning, artificial intelligence or deep learning, you might know what neural networks are. TensorFlow is a popular framework which can be used to implement efficient neural networks and deep learning models. This book will show you how to leverage the power of TensorFlow to train efficient neural networks. You will start with understanding the fundamentals and basic math for neural networks and why TensorFlow is a popular choice of tool for programming neural networks. During the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how it maps to the appropriate TensorFlow constructs.

Neural Network Programming with Tensorflow

Neural Network Programming with Tensorflow

If you're aware of the buzz surrounding the terms such as machine learning, artificial intelligence or deep learning, you might know what neural networks are. TensorFlow is a popular framework which can be used to implement efficient neural networks and deep learning models. This book will show you how to leverage the power of TensorFlow to train efficient neural networks. You will start with understanding the fundamentals and basic math for neural networks and why TensorFlow is a popular choice of tool for programming neural networks. During the course of the book, you will be working on real-world datasets to get a hands-on understanding of neural network programming. By the end of this book, you will have a fair understanding of how you can leverage the power of TensorFlow to train neural networks of varying complexities, without any hassle. While you are learning about various neural network implementations you will learn the underlying mathematics and linear algebra and how it maps to the appropriate TensorFlow constructs.

R Deep Learning Projects

R Deep Learning Projects

R is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. This book demonstrates end-to-end implementations of five real-world projects on popular topics in deep learning such as handwritten digit recognition, traffic light detection, fraud detection, text generation, and sentiment analysis. You'll see how to train effective neural networks in R—including convolutional neural networks, recurrent neural networks and LSTMs—and also see how neural networks can be trained using GPU capabilities. You will use popular R libraries and packages—such as MXNetR, H2O, deepnet, and more—to implement the projects. By the end of this book, you will have a better understanding of deep learning concepts and techniques and how to use them in a practical setting.

Feb 2018 8h 36m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.