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README
Apache-2.0

Deeplearning4J Examples

NOTE: HOW to interpret these examples

Data Loading

In this repository, you may likely see custom datasetiterators - these iterators are only for special examples and 1 off use cases. Consult the gitter if you are not sure how to proceed. Once you find a record reader for your use case, you then should use one of pre made iterators that knows how to interpret record reader output, either RecordReaderDataSetIterator for normal data or SequenceRecordReaderDataSetIterator for sequence data. For more on sequences, please see our rnns page

We have special iterators for 1 off use cases where normal data does not quite exist, or sometimes it is legacy. 99% of the time you should be using datavec and writing your own custom record readers if one of our pre provided ones is not suitable. If you are not sure what is available, please again consult the gitter - In general, you can find both normal record readers and sequence record readers in the datavec javadoc.

Dependencies

Note that this repository contains all dl4j examples for all modules. It will download about 1.5g of dependencies from maven central when you are first starting out. That being said, this makes it easier to get started without worrying about what to download. This examples repository is meant to be a reference point to get started with most common use cases. It is broken up in to modules. If you would like to just have a more minimal/simple, guide please go here

Repository of Deeplearning4J neural net examples:

  • MLP Neural Nets
  • Convolutional Neural Nets
  • Recurrent Neural Nets
  • TSNE
  • Word2Vec & GloVe
  • Anomaly Detection
  • User interface examples.

DL4J-Examples is released under an Apache 2.0 license. By contributing code to this repository, you agree to make your contribution available under an Apache 2.0 license.


Build and Run

Use Maven to build the examples.

mvn clean package

This downloads binaries for all platforms, but we can also append -Djavacpp.platform= with android-arm, android-x86, linux-ppc64le, linux-x86_64, macosx-x86_64, or windows-x86_64 to get binaries for only one platform and produce much smaller archives.

Run the runexamples.sh script to run the examples (requires bash). It will list the examples and prompt you for the one to run. Pass the --all argument to run all of them. (Other options are shown with -h).

./runexamples.sh [-h | --help]

Documentation

For more information, check out deeplearning4j.org and its JavaDoc.

GradientsListenerExample.java in dl4j-examples/src/main/java/org/deeplearning4j/examples/userInterface uses JavaFX. If you're using Java 8 or greater, it should run as is. If you're using Java 7 or an earlier version, you should set JAVAFX_HOME to point to the root directory of the JavaFX 2.0 SDK.

Other Issues

If you notice issues, please log them, and if you want to contribute, submit a pull request. Input is welcome here.

Copyright 2015-2019 Skymind Inc. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ########################## -- Misc files -- *README.md *readme.md .github/CONTRIBUTING.md .github/ISSUE_TEMPLATE.md .github/PULL_REQUEST_TEMPLATE.md org/deeplearning4j/examples/misc/customlayers/CustomLayerExampleReadme.md org/deeplearning4j/examples/tictactoe/ReadMe.txt lstm-hdfs/src/resources/test/f1 lstm-hdfs/src/resources/test/f2 lstm-hdfs/src/resources/train/f1 lstm-hdfs/src/resources/train/f2 lstm-hdfs/src/resources/train/f3 nd4j-examples/src/main/resources/numpy_cheatsheet/file.csv nd4j-examples/src/main/resources/numpy_cheatsheet/file.txt nd4j-examples/src/main/resources/numpy_cheatsheet/saveFile.csv nd4j-examples/src/main/resources/numpy_cheatsheet/saveFile.txt pydatavec-examples/basic_example.csv pydatavec-examples/reduction_example.csv rl4j-examples/cartpole.gif rl4j-examples/cliffwalk.gif rl4j-examples/cliffwalk_block.gif rl4j-examples/doom.gif rl4j-examples/scoregraph.png tutorials/00. Quickstart for Deeplearning4j.json tutorials/00. Quickstart for Deeplearning4j.zepp.ipynb tutorials/01. MultiLayerNetwork and ComputationGraph.json tutorials/01. MultiLayerNetwork and ComputationGraph.zepp.ipynb tutorials/02. Built-in Data Iterators.json tutorials/02. Built-in Data Iterators.zepp.ipynb tutorials/03. Logistic Regression.json tutorials/03. Logistic Regression.zepp.ipynb tutorials/04. Feed-forward.json tutorials/04. Feed-forward.zepp.ipynb tutorials/05. Basic Autoencoder- Anomaly Detection Using Reconstruction Error.json tutorials/05. Basic Autoencoder- Anomaly Detection Using Reconstruction Error.zepp.ipynb tutorials/06. Advanced Autoencoder- Trajectory Clustering using AIS.json tutorials/06. Advanced Autoencoder- Trajectory Clustering using AIS.zepp.ipynb tutorials/07. Convolutions- Train FaceNet Using Center Loss.json tutorials/07. Convolutions- Train FaceNet Using Center Loss.zepp.ipynb tutorials/08. RNNs- Sequence Classification of Synthetic Control Data.json tutorials/08. RNNs- Sequence Classification of Synthetic Control Data.zepp.ipynb tutorials/09. Early Stopping.ipynb tutorials/09. Early Stopping.zepp.json tutorials/10. Layers and Preprocessors.ipynb tutorials/10. Layers and Preprocessors.zepp.json tutorials/11. Hyperparameter Optimization.json tutorials/11. Hyperparameter Optimization.zepp.ipynb tutorials/12. Clinical Time Series LSTM Example.json tutorials/12. Clinical Time Series LSTM Example.zepp.ipynb tutorials/13. Clinical LSTM Time Series Example Using SKIL.json tutorials/13. Clinical LSTM Time Series Example Using SKIL.zepp.ipynb tutorials/14. Parallel Training.json tutorials/14. Parallel Training.zepp.ipynb tutorials/15. Sea Temperature Convolutional LSTM Example.json tutorials/15. Sea Temperature Convolutional LSTM Example.zepp.ipynb tutorials/16. Sea Temperature Convolutional LSTM Example 2.json tutorials/16. Sea Temperature Convolutional LSTM Example 2.zepp.ipynb tutorials/17. Instacart Multitask Example.json tutorials/17. Instacart Multitask Example.zepp.ipynb tutorials/18. Instacart Single Task Example.json tutorials/18. Instacart Single Task Example.zepp.ipynb tutorials/19. Cloud Detection Example.json tutorials/19. Cloud Detection Example.zepp.ipynb Copyright (c) 2015-2019 Skymind, Inc. Apache 2.0 License ##########################

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