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Merge pull request eugenp#7988 from alessiostalla/BAEL-18260
#BAEL-18260 Restructure ml and deeplearning4j modules
2 parents 2a746e6 + 8956aee commit 468c8e0

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‎deeplearning4j/README.md

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## Deeplearning4j
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This module contains articles about Deeplearning4j
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This module contains articles about Deeplearning4j.
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### Relevant Articles:
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- [A Guide to Deeplearning4j](https://www.baeldung.com/deeplearning4j)
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- [Logistic Regression in Java](https://www.baeldung.com/java-logistic-regression)

‎deeplearning4j/pom.xml

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</parent>
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<dependencies>
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<dependency>
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<groupId>org.nd4j</groupId>
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<artifactId>nd4j-api</artifactId>
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<version>${dl4j.version}</version>
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</dependency>
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<dependency>
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<groupId>org.nd4j</groupId>
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<artifactId>nd4j-native-platform</artifactId>
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<artifactId>deeplearning4j-core</artifactId>
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<version>${dl4j.version}</version>
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</dependency>
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<dependency>
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<groupId>org.deeplearning4j</groupId>
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<artifactId>deeplearning4j-nn</artifactId>
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<version>${dl4j.version}</version>
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</dependency>
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<!-- https://mvnrepository.com/artifact/org.datavec/datavec-api -->
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<dependency>
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<groupId>org.datavec</groupId>
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<artifactId>datavec-api</artifactId>
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<version>${dl4j.version}</version>
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</dependency>
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<dependency>
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<groupId>org.apache.httpcomponents</groupId>
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<artifactId>httpclient</artifactId>
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<version>4.3.5</version>
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</dependency>
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</dependencies>
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<properties>
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<dl4j.version>0.9.1</dl4j.version>
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<dl4j.version>0.9.1</dl4j.version> <!-- Latest non beta version -->
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</properties>
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</project>
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</project>

‎deeplearning4j/src/main/java/com/baeldung/deeplearning4j/IrisClassifier.java

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import org.datavec.api.records.reader.RecordReader;
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import org.datavec.api.records.reader.impl.csv.CSVRecordReader;
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import org.datavec.api.split.FileSplit;
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import org.datavec.api.util.ClassPathResource;
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import org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator;
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import org.deeplearning4j.eval.Evaluation;
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import org.deeplearning4j.nn.conf.BackpropType;
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import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
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import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
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import org.deeplearning4j.nn.conf.layers.DenseLayer;
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import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
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import org.nd4j.linalg.dataset.api.preprocessor.DataNormalization;
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import org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize;
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import org.nd4j.linalg.io.ClassPathResource;
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import org.nd4j.linalg.lossfunctions.LossFunctions;
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import java.io.IOException;
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.iterations(1000)
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.activation(Activation.TANH)
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.weightInit(WeightInit.XAVIER)
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.learningRate(0.1)
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.regularization(true).l2(0.0001)
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.regularization(true)
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.learningRate(0.1).l2(0.0001)
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.list()
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.layer(0, new DenseLayer.Builder().nIn(FEATURES_COUNT).nOut(3)
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.build())
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.layer(2, new OutputLayer.Builder(LossFunctions.LossFunction.NEGATIVELOGLIKELIHOOD)
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.activation(Activation.SOFTMAX)
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.nIn(3).nOut(CLASSES_COUNT).build())
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.backprop(true).pretrain(false)
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.backpropType(BackpropType.Standard).pretrain(false)
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.build();
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MultiLayerNetwork model = new MultiLayerNetwork(configuration);
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model.init();
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model.fit(trainingData);
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INDArray output = model.output(testData.getFeatureMatrix());
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INDArray output = model.output(testData.getFeatures());
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Evaluation eval = new Evaluation(CLASSES_COUNT);
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eval.eval(testData.getLabels(), output);

‎ml/src/main/java/com/baeldung/logreg/MnistClassifier.java renamed to ‎deeplearning4j/src/main/java/com/baeldung/logreg/MnistClassifier.java

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import org.datavec.image.loader.NativeImageLoader;
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import org.datavec.image.recordreader.ImageRecordReader;
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import org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator;
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import org.deeplearning4j.eval.Evaluation;
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import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
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import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
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import org.deeplearning4j.nn.conf.inputs.InputType;
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import org.deeplearning4j.nn.weights.WeightInit;
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import org.deeplearning4j.optimize.listeners.ScoreIterationListener;
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import org.deeplearning4j.util.ModelSerializer;
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import org.nd4j.evaluation.classification.Evaluation;
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import org.nd4j.linalg.activations.Activation;
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import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
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import org.nd4j.linalg.dataset.api.preprocessor.DataNormalization;
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import org.nd4j.linalg.dataset.api.preprocessor.ImagePreProcessingScaler;
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import org.nd4j.linalg.learning.config.Nesterovs;
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import org.nd4j.linalg.lossfunctions.LossFunctions;
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import org.nd4j.linalg.schedule.MapSchedule;
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import org.nd4j.linalg.schedule.ScheduleType;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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public class MnistClassifier {
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private static final Logger logger = LoggerFactory.getLogger(MnistClassifier.class);
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private static final String basePath = System.getProperty("java.io.tmpdir") + "mnist" + File.separator;
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private static final String basePath = System.getProperty("java.io.tmpdir") + File.separator + "mnist" + File.separator;
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private static final File modelPath = new File(basePath + "mnist-model.zip");
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private static final String dataUrl = "http://github.com/myleott/mnist_png/raw/master/mnist_png.tar.gz";
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String localFilePath = basePath + "mnist_png.tar.gz";
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File file = new File(localFilePath);
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if (!file.exists()) {
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file.getParentFile()
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.mkdirs();
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file.getParentFile().mkdirs();
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Utils.downloadAndSave(dataUrl, file);
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Utils.extractTarArchive(file, basePath);
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}
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.build();
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final MultiLayerConfiguration config = new NeuralNetConfiguration.Builder().seed(seed)
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.l2(0.0005) // ridge regression value
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.updater(new Nesterovs(new MapSchedule(ScheduleType.ITERATION, learningRateSchedule)))
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.updater(new Nesterovs()) //TODO new MapSchedule(ScheduleType.ITERATION, learningRateSchedule)
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.weightInit(WeightInit.XAVIER)
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.list()
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.layer(layer1)
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.layer(layer2)
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.layer(layer3)
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.layer(layer2)
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.layer(layer4)
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.layer(layer5)
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.layer(0, layer1)
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.layer(1, layer2)
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.layer(2, layer3)
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.layer(3, layer2)
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.layer(4, layer4)
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.layer(5, layer5)
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.setInputType(InputType.convolutionalFlat(height, width, channels))
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.build();
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ModelSerializer.writeModel(model, modelPath, true);
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logger.info("The MINIST model has been saved in {}", modelPath.getPath());
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}
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}
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}

‎ml/src/main/java/com/baeldung/logreg/MnistPrediction.java renamed to ‎deeplearning4j/src/main/java/com/baeldung/logreg/MnistPrediction.java

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‎ml/src/main/java/com/baeldung/logreg/Utils.java renamed to ‎deeplearning4j/src/main/java/com/baeldung/logreg/Utils.java

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‎ml/README.md

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‎ml/pom.xml

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‎ml/src/main/resources/logback.xml

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‎pom.xml

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<module>metrics</module>
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<!-- <module>micronaut</module> --> <!-- Fixing in BAEL-10877 -->
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<module>microprofile</module>
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<module>ml</module>
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<module>msf4j</module>
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<!-- <module>muleesb</module> --> <!-- Fixing in BAEL-10878 -->
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<module>mustache</module>
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<module>metrics</module>
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<!-- <module>micronaut</module> --> <!-- Fixing in BAEL-10877 -->
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<module>microprofile</module>
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<module>ml</module>
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<module>msf4j</module>
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<!-- <module>muleesb</module> --> <!-- Fixing in BAEL-10878 -->
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<module>mustache</module>

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