Deeplearning4j
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Introduction
Comprehensive documentation for Eclipse Deeplearning4j and its ecosystem — ND4J, SameDiff, DataVec, Keras Import, Python4J, and more
Listed on
July 22, 2026
What is Deeplearning4j?
Eclipse Deeplearning4j is an open-source, distributed deep learning framework for the JVM. It provides a complete ecosystem for building, training, and deploying neural networks in Java and Scala, with native GPU acceleration via CUDA and high-performance CPU computation via OpenBLAS and oneDNN.
How to use Deeplearning4j?
- To get started with Deeplearning4j, first review the Ecosystem Overview to understand how all the libraries fit together. Then follow the Quickstart guide to build and train your first neural network in 10 minutes. Add DL4J to your project using Maven Setup, and consult the Beginners Guide for learning resources and roadmap.
Core features of Deeplearning4j
- ND4J: N-dimensional array library (NumPy for Java)
- Deeplearning4j: Neural network training and inference
- SameDiff: Automatic differentiation and graph execution
- DataVec: Data loading, transformation, and ETL
- Model Import: Import models from Keras, TensorFlow, ONNX
- Python4J: Python interop from Java via CPython embedding
- OmniHub: Pretrained model registry
- Arbiter: Hyperparameter optimization
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