Dr. Joshua F. Wiley's R Deep Learning Essentials PDF

By Dr. Joshua F. Wiley

ISBN-10: 1785280589

ISBN-13: 9781785280580

Key Features

  • Harness the power to construct algorithms for unsupervised information utilizing deep studying recommendations with R
  • Master the typical difficulties confronted akin to overfitting of knowledge, anomalous datasets, picture popularity, and function tuning whereas construction the models
  • Build versions in relation to neural networks, prediction and deep prediction

Book Description

Deep studying is a department of computing device studying in line with a collection of algorithms that try and version high-level abstractions in information by utilizing version architectures. With the excellent reminiscence administration and the total integration with multi-node colossal facts structures, the H2O engine has develop into a growing number of well known between info scientists within the box of deep learning.

This ebook will introduce you to the deep studying package deal H2O with R and assist you comprehend the strategies of deep studying. we are going to begin via establishing very important deep studying applications on hand in R after which circulation in the direction of construction versions on the topic of neural networks, prediction, and deep prediction, all of this with assistance from real-life examples.

After fitting the H2O package deal, you are going to know about prediction algorithms. relocating forward, options comparable to overfitting info, anomalous info, and deep prediction types are defined. ultimately, the booklet will disguise recommendations on the subject of tuning and optimizing models.

What you'll learn

  • Set up the R package deal H2O to coach deep studying models
  • Understand the center recommendations at the back of deep studying models
  • Use Autoencoders to spot anomalous information or outliers
  • Predict or classify facts immediately utilizing deep neural networks
  • Build generalizable types utilizing regularization to prevent overfitting the educational data

About the Author

Dr. Joshua F. Wiley is a lecturer at Monash collage and a senior associate at Elkhart staff restricted, a statistical consultancy. He earned his PhD from the college of California, la. His learn specializes in utilizing complex quantitative tips on how to comprehend the advanced interplays of mental, social, and physiological tactics relating to mental and actual well-being. In records and knowledge technological know-how, Joshua specializes in biostatistics and is attracted to reproducible examine and graphical monitors of information and statistical types. via consulting at Elkhart crew restricted and his former paintings on the UCLA Statistical Consulting staff, Joshua has helped a wide range of consumers, starting from skilled researchers to biotechnology businesses. He develops or codevelops a few R programs together with varian, a package deal to behavior Bayesian scale-location structural equation types, and MplusAutomation, a favored package deal that hyperlinks R to the industrial Mplus software.

Table of Contents

  1. Getting all 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

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R Deep Learning Essentials by Dr. Joshua F. Wiley


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