Deeplearning4j
Deeplearning4j is an open-source, distributed deep learning library for Java and Scala. It is designed to be used in business environments, rather than academic research.
deep-learning
neural-networks
java
scala
Deeplearning4j: Open-Source Distributed Deep Learning Library for Java & Scala
An open-source, distributed deep learning library designed for business use in Java and Scala, rather than academic research.
What is Deeplearning4j?
Deeplearning4j (DL4J) is an open-source, distributed deep learning library written for Java and Scala. It is designed with enterprise use cases in mind, with features like multi-GPU and multi-CPU support built-in.
Some key things to know about Deeplearning4j:
- Implemented in Java and Scala, runs on the JVM
- Focused on ease of use and integration for industry use cases
- Supports neural networks, convolutional nets, recurrent nets, LSTMs, word2vec, doc2vec
- Distributed across GPUs and machines (spark), allows scaling up deep learning
- Compatible with frameworks like Spark, Hadoop, Kafka, Aerospike, Redis
Deeplearning4j aims to bring production-quality deep learning to industry through its focus on parallelization and optimizers suited for business environments. Its workflow and terminology draws similarities with deep learning Python frameworks like Keras, but the underlying design patterns are tailored for JVM integration.
Deeplearning4j Features
Features
- Supports neural networks and deep learning architectures
- Includes convolutional nets, recurrent nets, LSTMs, autoencoders and more
- Runs on distributed GPUs and CPUs
- Integrates with Spark and Hadoop for distributed training
- Supports importing models from Keras and TensorFlow
- APIs for Java, Scala, Clojure and Kotlin
Pricing
- Open Source
Pros
Open source and free to use
Good documentation and active community support
Scales well for distributed training
Integrates with big data tools like Spark and Hadoop
Supports multiple JVM languages
Cons
Not as full-featured as TensorFlow or PyTorch
Limited selection of pre-trained models
Not as widely used as some other frameworks
Official Links
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