dl4j-examples This project contains a set of examples that demonstrate use of the high level DL4J API to build a variety of neural networks. Some of these examples are end to end, in the sense they start with raw data, process it and then build and train neural networks on it. tensorflow-keras-import-examples This project contains a set of examples that demonstrate how to import Keras h5 models and TensorFlow frozen pb models into the DL4J ecosystem.
Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs.
1. DataPrepare Deeplearning4j works with a lot of different data types, such as images, CSV, plain text, images, audio, video and, pretty much any other data type you can think of.
.1. RecordReader .2. DataSetIterator ScoreIterationListener - (Source, Javadoc) - Logs the loss function score every N training iterations PerformanceListener - (Source, Javadoc) - Logs performance (examples per sec, minibatches per sec, ETL time), and optionally score, every N training iterations.
