- Does Deep Netts library have support for GPU?
- Does Deep Netts have support for distributed training?
- Is Deep Netts library slow without GPU/distributed computing support?
- How does Deep Netts library compares to the other deep learning solutions available in Java?
- Why/when should I use Deep Netts?
- Can I use Deep Netts tools with other deep learning frameworks?
- How much data can Deep Netts process efficiently?
1. Does Deep Netts Library have support for GPU?
Not at the moment, but there is an ongoing development to add GPU support.
2. Does Deep Netts have support for distributed training?
Not directly through its own deep learning library, it will be able to support it through third-party frameworks.
3. Is Deep Netts library slow without GPU/distributed computing support?
It can be slow for large amounts of data for complex problems, but in some cases, it can be more effective than GPU/distributed solutions in both performance and cost.
4. How does Deep Netts library compares to the other deep learning solutions available in Java?
|Framework / Library||Strengths||Weakness||JSR 381 support||Commercial support available||License|
|TensorFlow for Java||High performance, GPU support, direct use of models created in Python.||Java API experimental, not actively supported. Not so easy-to-use. Difficult for beginners, even experienced dev, very unintuitive for Java developers.||No||No||Apache 2.0|
|DeepNetts||Pure Java, intuitive API, easy to use for beginners, RI for standard Java API JSR381||No GPU or Distributed support at the moment is a limitation for large scale data sets.||Yes||Yes||GPL with CPE|
|DL4J||Supports many types of architectures, GPU, distributed training with Spark.||Not very friendly API, hard to follow and understand for non-experts and beginners.||No||Yes||Apache 2.0|
|DJL||Framework agnostic, support for standard Java API JSR381.||Mainly a wrapper for other existing libraries (MXNet, but TensorFlow and PyTorch support coming).||Yes||No||Apache 2.0|
5. Why/when should I use Deep Netts Library?
The Deep Netts is a perfect fit if you require:
– pure java deep learning solution
– easy to integrate, distribute and maintain deep learning solution
– smaller and mid-scale machine learning problems (in terms of data) with large scale deployment
– easy to use for users with less experience with machine learning
– friendly tools for users with software development background
6. Can I use Deep Netts tools with other deep learning frameworks?
Technically yes, the Deep Netts development tool is able to support any 3rd party deep learning framework. The Tensorflow support is under development, and if you’re interested in commercial development for support for some other framework please let us know.
7. How much data can the Deep Netts process efficiently?
Impossible to say since it depends of the problem complexity and size of the model. Best way to check this is to try with Free 30 Day Trial