Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
R Deep Learning Essentials

Buy
R Deep Learning Essentials, 9781785280580 (1785280589), Packt Publishing, 2016

Key Features

  • Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
  • Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
  • Build models relating to neural networks, prediction and deep prediction

Book Description

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with multi-node big data platforms, the H2O engine has become more and more popular among data scientists in the field of deep learning.

This book will introduce you to the deep learning package H2O with R and help you understand the concepts of deep learning. We will start by setting up important deep learning packages available in R and then move towards building models related to neural networks, prediction, and deep prediction, all of this with the help of real-life examples.

After installing the H2O package, you will learn about prediction algorithms. Moving ahead, concepts such as overfitting data, anomalous data, and deep prediction models are explained. Finally, the book will cover concepts relating to tuning and optimizing models.

What you will learn

  • Set up the R package H2O to train deep learning models
  • Understand the core concepts behind deep learning models
  • Use Autoencoders to identify anomalous data or outliers
  • Predict or classify data automatically using deep neural networks
  • Build generalizable models using regularization to avoid overfitting the training data

About the Author

Dr. Joshua F. Wiley is a lecturer at Monash University and a senior partner at Elkhart Group Limited, a statistical consultancy. He earned his PhD from the University of California, Los Angeles. His research focuses on using advanced quantitative methods to understand the complex interplays of psychological, social, and physiological processes in relation to psychological and physical health. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. Through consulting at Elkhart Group Limited and his former work at the UCLA Statistical Consulting Group, Joshua has helped a wide array of clients, ranging from experienced researchers to biotechnology companies. He develops or codevelops 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.

Table of Contents

  1. Getting Started with Deep Learning
  2. Training a Prediction Model
  3. Preventing Overfitting
  4. Identifying Anomalous Data
  5. Training Deep Prediction Models
  6. Tuning and Optimizing Models
  7. Bibliography
(HTML tags aren't allowed.)

Applications of Symmetry Methods to Partial Differential Equations (Applied Mathematical Sciences)
Applications of Symmetry Methods to Partial Differential Equations (Applied Mathematical Sciences)

This is an accessible book on the advanced symmetry methods for differential equations. Subjects such as conservation laws, Lie-Bäcklund symmetries, contact transformations, adjoint symmetries, Nöther's Theorem, mappings with some modification, potential symmetries, nonlocal symmetries, nonlocal mappings, and non-classical...

Doing Objects in Visual Basic 2005 (The Addison-Wesley Microsoft Technology Series)
Doing Objects in Visual Basic 2005 (The Addison-Wesley Microsoft Technology Series)
Welcome to the latest in the series of Doing Objects books. This series started in 1995 with Visual Basic 4.0, when VB could first do objects. At that time, little had been discussed about using object-oriented design and development techniques with Visual Basic. To help improve that situation, almost half of each book in the series was...
Fundamentals of Computer Architecture and Design
Fundamentals of Computer Architecture and Design

This textbook provides semester-length coverage of computer architecture and design, providing a strong foundation for students to understand modern computer system architecture and to apply these insights and principles to future computer designs.  



It is based on the author’s decades of industrial experience
...

Techno Rebels: The Renegades of Electronic Funk (Painted Turtle)
Techno Rebels: The Renegades of Electronic Funk (Painted Turtle)

When it was originally published in 1999, Techno Rebels became the definitive text on a hard-to-define but vital genre of music. Author Dan Sicko demystified techno's characteristics, influences, and origins and argued that although techno enjoyed its most widespread popularity in Europe, its birthplace and most important incubator was...

Vba for Excel Made Simple (Made Simple Programming)
Vba for Excel Made Simple (Made Simple Programming)
This book provides an introduction to VBA for Excel for new users. It covers basic concepts of VBA and of macro programming, and takes the reader through the process of constructing interactive working applications. Features which make it particularly suitable for new and non-technical users are: * step-by-step approach * avoidance of jargon *...
Image-Based Modeling
Image-Based Modeling

“This book guides you in the journey of 3D modeling from the theory with elegant mathematics to applications with beautiful 3D model pictures. Written in a simple, straightforward, and concise manner, readers will learn the state of the art of 3D reconstruction and modeling.” —Professor Takeo Kanade, Carnegie Mellon...

©2019 LearnIT (support@pdfchm.net) - Privacy Policy