Advanced Deep Learning with R Book [PDF] Download

Download the fantastic book titled Advanced Deep Learning with R written by Bharatendra Rai, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Advanced Deep Learning with R", which was released on 17 December 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Advanced Deep Learning with R by Bharatendra Rai PDF

Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key FeaturesImplement deep learning algorithms to build AI models with the help of tips and tricksUnderstand how deep learning models operate using expert techniquesApply reinforcement learning, computer vision, GANs, and NLP using a range of datasetsBook Description Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data. Advanced Deep Learning with R will help you understand popular deep learning architectures and their variants in R, along with providing real-life examples for them. This deep learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural networks, deep learning architectures, and the fundamentals for implementing deep learning with R. The book will also take you through using important deep learning libraries such as Keras-R and TensorFlow-R to implement deep learning algorithms within applications. You will get up to speed with artificial neural networks, recurrent neural networks, convolutional neural networks, long short-term memory networks, and more using advanced examples. Later, you'll discover how to apply generative adversarial networks (GANs) to generate new images; autoencoder neural networks for image dimension reduction, image de-noising and image correction and transfer learning to prepare, define, train, and model a deep neural network. By the end of this book, you will be ready to implement your knowledge and newly acquired skills for applying deep learning algorithms in R through real-world examples. What you will learnLearn how to create binary and multi-class deep neural network modelsImplement GANs for generating new imagesCreate autoencoder neural networks for image dimension reduction, image de-noising and image correctionImplement deep neural networks for performing efficient text classificationLearn to define a recurrent convolutional network model for classification in KerasExplore best practices and tips for performance optimization of various deep learning modelsWho this book is for This book is for data scientists, machine learning practitioners, deep learning researchers and AI enthusiasts who want to develop their skills and knowledge to implement deep learning techniques and algorithms using the power of R. A solid understanding of machine learning and working knowledge of the R programming language are required.


Detail About Advanced Deep Learning with R PDF

  • Author : Bharatendra Rai
  • Publisher : Packt Publishing Ltd
  • Genre : Computers
  • Total Pages : 339 pages
  • ISBN : 1789534984
  • PDF File Size : 42,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Advanced Deep Learning with R

Advanced Deep Learning with R
  • Publisher : Packt Publishing Ltd
  • File Size : 27,5 Mb
  • Release Date : 17 December 2019
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Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key FeaturesImplement deep learning algorithms to build AI models with the help of

Deep Learning with R

Deep Learning with R
  • Publisher : Springer
  • File Size : 49,9 Mb
  • Release Date : 13 April 2019
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Deep Learning with R introduces deep learning and neural networks using the R programming language. The book builds on the understanding of the theoretical and mathematical constructs and enables the

Advanced Machine Learning with R

Advanced Machine Learning with R
  • Publisher : Unknown Publisher
  • File Size : 54,9 Mb
  • Release Date : 16 May 2019
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Master machine learning techniques with real-world projects that interface TensorFlow with R, H2O, MXNet, and other languages Key Features Gain expertise in machine learning, deep learning and other techniques

Deep Learning with R, Second Edition

Deep Learning with R, Second Edition
  • Publisher : Simon and Schuster
  • File Size : 20,5 Mb
  • Release Date : 13 September 2022
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Deep learning from the ground up using R and the powerful Keras library! In Deep Learning with R, Second Edition you will learn: Deep learning from first principles Image classification

Hands-On Machine Learning with R

Hands-On Machine Learning with R
  • Publisher : CRC Press
  • File Size : 23,5 Mb
  • Release Date : 07 November 2019
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Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’

Deep Learning with R

Deep Learning with R
  • Publisher : Simon and Schuster
  • File Size : 54,8 Mb
  • Release Date : 22 January 2018
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Summary Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through

Deep Learning with R

Deep Learning with R
  • Publisher : Pearson Professional
  • File Size : 33,5 Mb
  • Release Date : 16 June 2024
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Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples.

Neural Networks with R

Neural Networks with R
  • Publisher : Packt Publishing Ltd
  • File Size : 20,8 Mb
  • Release Date : 27 September 2017
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Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your

Introduction to Deep Learning Using R

Introduction to Deep Learning Using R
  • Publisher : Apress
  • File Size : 23,5 Mb
  • Release Date : 19 July 2017
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Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development

Hands-On Deep Learning with R

Hands-On Deep Learning with R
  • Publisher : Packt Publishing Ltd
  • File Size : 48,6 Mb
  • Release Date : 24 April 2020
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Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and Deepnet Key FeaturesUnderstand deep learning algorithms and architectures using