deeplearning4j-examples

Why we included this project

For teams building deep learning applications on the JVM, this is the official collection of runnable examples for the Eclipse Deeplearning4J ecosystem. Each example sits in its own Maven project and walks through one slice of the workflow: loading and cleaning data with DataVec, assembling networks with the high-level DL4J API, doing NumPy-style array work with ND4J, and dropping down to SameDiff when you need explicit auto-differentiation. You also get working code for importing Keras models (including tf.keras), distributed training on Apache Spark, and multi-GPU data-parallel setups. The projects separate quickstarts from advanced examples and lay out a suggested reading order, so a newcomer can start from a clean working sample instead of guessing where to begin.