CRAN

deepNN 0.3

Deep Learning

Released Mar 8, 2019 by Benjamin Taylor

Dependencies

Matrix 1.2-16

Implementation of some Deep Learning methods. Includes multilayer perceptron, different activation functions, regularisation strategies, stochastic gradient descent and dropout. Thanks go to the following references for helping to inspire and develop the package: Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach (2016, ISBN:978-0262035613) Deep Learning. Terrence J. Sejnowski (2018, ISBN:978-0262038034) The Deep Learning Revolution. Grant Sanderson (3brown1blue) Neural Networks YouTube playlist. Michael A. Nielsen Neural Networks and Deep Learning.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>deepNN</artifactId>
    <version>0.3-b1</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:deepNN')

Test Results

This package was last tested against Renjin 0.9.2724 on Mar 10, 2019.

• L1_regularisation-examples
• L2_regularisation-examples
• NNgrad_test-examples
• NNpredict-examples
• Qloss-examples
• ReLU-examples
• hyptan-examples
• ident-examples
• logistic-examples
• nbiaspar-examples
• net_test
• network-examples
• nnetpar-examples
• no_regularisation-examples
• smoothReLU-examples
• softmax-examples
• train-examples
• wQloss-examples

Source

View GitHub Mirror

Release History

• 0.3