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GeezerVison is showing github.com — GitHub - PacktPublishing/Java-Deep-Learning-Cookbook: Java Deep Learning Cookbook, published by Packt

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01_Introduction_to_Deep_Learning_in_Java
01_Introduction_to_Deep_Learning_in_Java
 
 
02_Data_Extraction_Transform_and_Loading
02_Data_Extraction_Transform_and_Loading
 
 
03_Building_Deep_Neural_Networks_for_Binary_classification
03_Building_Deep_Neural_Networks_for_Binary_classification
 
 
04_Building_Convolutional_Neural_Networks
04_Building_Convolutional_Neural_Networks
 
 
05_Implementing_NLP
05_Implementing_NLP
 
 
06_Constructing_LSTM_Network_for_time_series
06_Constructing_LSTM_Network_for_time_series
 
 
07_Constructing_LSTM_Neural_network_for_sequence_classification
07_Constructing_LSTM_Neural_network_for_sequence_classification
 
 
08_Performing_Anomaly_detection_on_unsupervised data
08_Performing_Anomaly_detection_on_unsupervised data
 
 
09_Using_RL4J_for_Reinforcement learning
09_Using_RL4J_for_Reinforcement learning
 
 
10_Developing_applications_in_distributed_environment
10_Developing_applications_in_distributed_environment
 
 
11_Applying_Transfer_Learning_to_network_models
11_Applying_Transfer_Learning_to_network_models
 
 
12_Benchmarking_and_Neural_Network_Optimization
12_Benchmarking_and_Neural_Network_Optimization
 
 
.gitignore
.gitignore
 
 
CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 

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Java deep learning cookbook

Java Deep Learning Cookbook

This is a code repository for the upcoming book "Java Deep Learning cookbook" sponsored by Packt Publishing. We use and promote deeplearning4j library for all use-cases in this book. Official deeplearning4j version targeted in this cookbook is 1.0.0-beta3. For the same reason, some of the methods or approaches discussed in this cookbook may get deprecated in their newer versions. So, be sure to refer their latest API documentation. You may use newer versions that has bug fixes and new features.

Update

Java deep learning cookbook is released on November 8, 2019.

Build

Each chapter will have separate source folder where all examples are stored for the particular chapter. For example, if you want to import the code for chapter 2, navigate to the chapter directory first and then import the directory sourceCode/cookbook-app in your IDE. You should also see pom.xml located there.

cookbookworkspace

From Intellij IDE

  • Navigate to the sourceCode root directory.
  • Open as a Maven project and compile.

From Command Line

mvn clean install

If you face issues with Intellij being not able to detect dependencies or any workspace issues, try running the below command:

mvn idea:idea

Delete workspace.xml under .idea directory if problem persists.

Table of Contents

  1. Introduction to Deep Learning in Java
  2. Data Extraction, Transform and Loading
  3. Building Deep Neural Networks for Binary classification
  4. Building Convolutional Neural Networks
  5. Implementing NLP
  6. Constructing LTSM Network for time series
  7. Constructing LTSM Neural network for sequence classification
  8. Performing Anomaly detection on unsupervised data
  9. Using RL4J for Reinforcement learning
  10. Developing applications in distributed environment
  11. Applying Transfer Learning to network models
  12. Benchmarking and Neural Network Optimization

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781788995207

About

Java Deep Learning Cookbook, published by Packt

Topics

artificial-intelligenceartificial-neural-networksclassificationcookbookdeep-learningdeeplearningdeeplearning4jjavajava-machine-learningmachine-learningmachinelearningneural-networknlpreinforcement-learningtime-series

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