Search icon Close icon
Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Deep Learning Essentials. - Second Edition

You're reading from  R Deep Learning Essentials. - Second Edition

Product type Book
Published in Aug 2018
Publisher Packt
ISBN-13 9781788992893
Pages 378 pages
Edition 2nd Edition
Languages
Concepts
Authors (2):
Mark Hodnett Mark Hodnett
Profile icon Mark Hodnett
LinkedIn
Mark Hodnett is a data scientist with over 20 years of industry experience in software development, business intelligence systems, and data science. He has worked in a variety of industries, including CRM systems, retail loyalty, IoT systems, and accountancy. He holds a master's in data science and an MBA. He works in Cork, Ireland, as a senior data scientist with AltViz.
Read more
See other products by Mark Hodnett
Joshua F. Wiley Joshua F. Wiley
Profile icon Joshua F. Wiley
LinkedIn
Joshua F. Wiley is a lecturer at Monash University, conducting quantitative research on sleep, stress, and health. He earned his Ph.D. from the University of California, Los Angeles and completed postdoctoral training in primary care and prevention. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. He develops or co-develops a number of R packages including Varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.
Read more
See other products by Joshua F. Wiley
View More author details
Toc

Table of Contents (13) Chapters close

Preface 1. Getting Started with Deep Learning 2. Training a Prediction Model 3. Deep Learning Fundamentals 4. Training Deep Prediction Models 5. Image Classification Using Convolutional Neural Networks 6. Tuning and Optimizing Models 7. Natural Language Processing Using Deep Learning 8. Deep Learning Models Using TensorFlow in R 9. Anomaly Detection and Recommendation Systems 10. Running Deep Learning Models in the Cloud 11. The Next Level in Deep Learning 12. Other Books You May Enjoy

Deep Learning Models Using TensorFlow in R

This chapter is about using TensorFlow in R. We have already used TensorFlow quite a lot, as Keras is a high-level neural network API that uses either TensorFlow, CNTK, or Theano. In R, Keras uses TensorFlow in the background. TensorFlow is more difficult to develop deep learning models in. However, there are two interesting packages in TensorFlow that could be overlooked: TensorFlow estimators and TensorFlow runs. We will cover both of these packages in this chapter.

In this chapter, we will cover the following topics:

  • Introduction to TensorFlow
  • Building models using TensorFlow
  • TensorFlow estimators
  • TensorFlow runs packages
lock icon The rest of the chapter is locked
arrow left Previous Section
Section 1 of 5
Next Section arrow right
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.
Sign up now
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 €14.99/month. Cancel anytime}

Authors (2)

Left arrow icon
Profile icon Mark Hodnett
LinkedIn
Mark Hodnett is a data scientist with over 20 years of industry experience in software development, business intelligence systems, and data science. He has worked in a variety of industries, including CRM systems, retail loyalty, IoT systems, and accountancy. He holds a master's in data science and an MBA. He works in Cork, Ireland, as a senior data scientist with AltViz.
Read more
See other products by Mark Hodnett
Profile icon Joshua F. Wiley
LinkedIn
Joshua F. Wiley is a lecturer at Monash University, conducting quantitative research on sleep, stress, and health. He earned his Ph.D. from the University of California, Los Angeles and completed postdoctoral training in primary care and prevention. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. He develops or co-develops a number of R packages including Varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.
Read more
See other products by Joshua F. Wiley
Right arrow icon

Other recommended products

Related to this chapter
Left arrow icon
Advanced Deep Learning with R
Advanced Deep Learning with R
Read more
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.
Read more
Dec 2019 11 hours 44 minutes
Deep Learning with R Cookbook
Deep Learning with R Cookbook
Read more
This book will help you get through the problems that you face during the execution of different tasks and understand hacks in deep learning. With unique recipes, you will implement various deep learning architectures using R 3.5.x. You will cover complex algorithms to perform tasks such as reinforcement learning, GANs, advanced neural networks and more.
Read more
Feb 2020 10 hours 56 minutes
R Deep Learning Projects
R Deep Learning Projects
Read more
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.
Read more
Feb 2018 8 hours 36 minutes
R Deep Learning Cookbook
R Deep Learning Cookbook
Read more
Deep Learning is the next big thing. It is a part of machine learning. Its favorable results in application with huge and complex data is remarkable. This book will help you to get through the problems that you face during the execution of different tasks and understand hacks in deep learning, neural networks, and advanced machine learning techniques
Read more
Aug 2017 9 hours 36 minutes
Hands-On Deep Learning with R
Hands-On Deep Learning with R
Read more
Deep learning enables efficient and accurate learning from data. Developers working with R will be able to put their knowledge to work with this practical guide to deep learning. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time.
Read more
Apr 2020 11 hours 0 minutes
Deep Learning with PyTorch
Deep Learning with PyTorch
Read more
This book provides the intuition behind the state of the art Deep Learning architectures such as ResNet, DenseNet, Inception, and encoder-decoder without diving deep into the math of it. It shows how you can implement and use various architectures to solve problems in the area of image classification, language translation and NLP using PyTorch.
Read more
Feb 2018 8 hours 44 minutes
R Machine Learning Projects
R Machine Learning Projects
Read more
The purpose of the book is to help a machine learning practitioner gets hands-on experience in working with real-world data and apply modern machine learning algorithms. You will learn to implement each algorithm to a specific industry problem. It covers projects involving both supervised as well as unsupervised learning approaches.
Read more
Jan 2019 11 hours 8 minutes
TensorFlow 2.0 Quick Start Guide
TensorFlow 2.0 Quick Start Guide
Read more
TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks.
Read more
Mar 2019 6 hours 32 minutes
Python Deep Learning Cookbook
Python Deep Learning Cookbook
Read more
Deep Learning is a rapidly evolving field of Machine Learning science which gives machines the ability to learn from information. This book contains detailed recipes to tackle with the common and not so common problems while dealing with deep learning algorithms and models in Python. You will benefit from this book by finding technical solutions to the issues presented, along with a detailed explanation of the solutions, and a discussion on corresponding pros and cons of implementing the proposed solution using Theano, Tensorflow, MXNet, and Keras. You'll come across recipes on data pre-processing, network models and topologies, supervised and unsupervised learning presented in a “solution to problem” fashion.
Read more
Oct 2017 11 hours 0 minutes
The Applied TensorFlow and Keras Workshop
The Applied TensorFlow and Keras Workshop
Read more
The Applied TensorFlow and Keras Workshop provides you with a blueprint to build an application that generates predictions using a deep learning model. You’ll learn to apply techniques to improve the model: add more data and features, change its architecture, or create a new model by changing the core components to meet your own requirements.
Read more
Jul 2020 5 hours 48 minutes
Beginning Application Development with TensorFlow and Keras
Beginning Application Development with TensorFlow and Keras
Read more
With this book, you’ll learn how to train, evaluate and deploy Tensorflow and Keras models as real-world web applications. After a hands-on introduction, you’ll use a sample model to explore the details of deep learning, selecting the right layers that can solve a given problem. By the end of the book, you’ll build a Bitcoin application that predicts the future price, based on historic, and freely available information.
Read more
May 2018 4 hours 56 minutes
Hands-On Computer Vision with TensorFlow 2
Hands-On Computer Vision with TensorFlow 2
Read more
Computer vision is achieving a new frontier of capabilities in fields like health, automobile or robotics. This book explores TensorFlow 2, Google's open-source AI framework, and teaches how to leverage deep neural networks for visual tasks. It will help you acquire the insight and skills to be a part of the exciting advances in computer vision.
Read more
May 2019 12 hours 24 minutes
Right arrow icon

Personalised recommendations for you

Based on your interests and search pattern
Left arrow icon
Et al.
Et al.
Read more
Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.
Read more
Aug 2023 7 hours 40 minutes
Generative AI with LangChain
Generative AI with LangChain
Read more
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Read more
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
Read more
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Read more
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
Read more
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Read more
Dec 2023 12 hours 0 minutes
Generative AI with LangChain
Generative AI with LangChain
Read more
This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.
Read more
Dec 2023 12 hours 0 minutes
Mastering Tableau 2023
Mastering Tableau 2023
Read more
This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.
Read more
Aug 2023 22 hours 48 minutes
Building AI Applications with ChatGPT APIs
Building AI Applications with ChatGPT APIs
Read more
This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.
Read more
Sep 2023 8 hours 36 minutes
Building AI Applications with ChatGPT APIs
Building AI Applications with ChatGPT APIs
Read more
This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.
Read more
Sep 2023 8 hours 36 minutes
Data Engineering with AWS
Data Engineering with AWS
Read more
Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.
Read more
Oct 2023 21 hours 12 minutes
Modern Data Architecture on AWS
Modern Data Architecture on AWS
Read more
Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.
Read more
Aug 2023 14 hours 0 minutes
Practical Guide to Applied Conformal Prediction in Python
Practical Guide to Applied Conformal Prediction in Python
Read more
Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.
Read more
Dec 2023 8 hours 0 minutes
TinyML Cookbook
TinyML Cookbook
Read more
With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.
Read more
Nov 2023 22 hours 8 minutes
Right arrow icon