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JS-Torch VS Deeplearning4j

Compare JS-Torch VS Deeplearning4j and see what are their differences

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JS-Torch logo JS-Torch

JS-Torch is a Deep Learning JavaScript library built from scratch, to closely follow PyTorch's syntax.

Deeplearning4j logo Deeplearning4j

Deeplearning4j is an open-source, distributed deep-learning library written for Java and Scala.
Not present
  • Deeplearning4j Landing page
    Landing page //
    2023-10-16

JS-Torch features and specs

No features have been listed yet.

Deeplearning4j features and specs

  • Java Integration
    Deeplearning4j is written for Java, making it easy to integrate with existing Java applications. This is a significant advantage for businesses running Java systems.
  • Scalability
    It is designed for scalability and can be used in distributed environments. This is ideal for handling large-scale datasets and heavy computational tasks.
  • Commercial Support
    Deeplearning4j offers professional support through commercial entities, which can be beneficial for enterprises needing reliable assistance and maintenance.
  • Compatibility with Hardware
    It provides compatibility with GPUs and various processing environments, allowing efficient training of deep networks.
  • Ecosystem
    Deeplearning4j is part of a larger ecosystem, including tools like DataVec for data preprocessing and ND4J for numerical computing, providing a comprehensive suite for machine learning tasks.

Possible disadvantages of Deeplearning4j

  • Learning Curve
    It can have a steep learning curve, especially for developers not already familiar with the Java programming language or deep learning concepts.
  • Community Size
    The community and available resources are not as extensive as those for other deep learning libraries like TensorFlow or PyTorch. This might limit access to free and diverse community support.
  • Less Popularity
    Compared to more popular frameworks like TensorFlow or PyTorch, Deeplearning4j is less commonly used, which may affect library updates and third-party tool integrations.
  • Performance
    In some use cases, performance can lag behind other optimized frameworks that extensively use C++ and CUDA, particularly for specific models or complex operations.

JS-Torch videos

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Deeplearning4j videos

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Deep Learning with DeepLearning4J and Spring Boot - Artur Garcia & Dimas Cabré @ Spring I/O 2017

Category Popularity

0-100% (relative to JS-Torch and Deeplearning4j)

JS-Torch

Deeplearning4j

Data Science Tools
35 35%
Data Science Tools
65% 65
Data Science And Machine Learning
16 16%
Data Science And Machine Learning
84% 84
Machine Learning
19 19%
Machine Learning
81% 81
AI
36 36%
AI
64% 64

User comments

Share your experience with using JS-Torch and Deeplearning4j. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Deeplearning4j seems to be more popular. It has been mentiond 5 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

JS-Torch mentions (0)

We have not tracked any mentions of JS-Torch yet. Tracking of JS-Torch recommendations started around Apr 2025.

Deeplearning4j mentions (5)

  • DeepLearning4j Blockchain Integration: Merging AI and Blockchain for a Transparent Future
    DeepLearning4j Blockchain Integration is more than just a convergence of technologies; it’s a paradigm shift in how AI projects are developed, funded, and maintained. By utilizing the robust framework of DL4J, enhanced with secure blockchain features and an inclusive open source model, the project is not only pushing the boundaries for artificial intelligence but also establishing a resilient model for future... - Source: dev.to / about 2 months ago
  • Machine Learning in Kotlin (Question)
    While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features. Source: over 3 years ago
  • Does Java has similar project like this one in C#? (ml, data)
    Would recommend taking a look at dl4j: https://deeplearning4j.org. Source: almost 4 years ago
  • just released my Clojure AI book
    We use DeepLearning4j in this chapter because it is written in Java and easy to use with Clojure. In a later chapter we will use the Clojure library libpython-clj to access other deep learning-based tools like the Hugging Face Transformer models for question answering systems as well as the spaCy Python library for NLP. Source: almost 4 years ago
  • [D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
    FastAPI. Or even simpler: DL4J, to be used in Java when we need to communicate with the rest of the applications in real time. Source: about 4 years ago

What are some alternatives?

When comparing JS-Torch and Deeplearning4j, you can also consider the following products

tinygrad - This may not be the best deep learning framework, but it is a deep learning framework.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

micrograd - A tiny Autograd engine (with a bite! :)).

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

TFlearn - TFlearn is a modular and transparent deep learning library built on top of Tensorflow.

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