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BigDL VS Deeplearning4j

Compare BigDL VS Deeplearning4j and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

BigDL logo BigDL

BigDL is a distributed deep learning library for Apache Spark.

Deeplearning4j logo Deeplearning4j

Deeplearning4j is an open-source, distributed deep-learning library written for Java and Scala.
  • BigDL Landing page
    Landing page //
    2023-10-16
  • Deeplearning4j Landing page
    Landing page //
    2023-10-16

BigDL 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.

BigDL videos

+ Add

BigDL app Review for Android - Free money for doing pretty much nothing!

More videos:

  • Review - 1 - BigDL Introduction - Getting Started
  • Review - BigDL Overview | Intel Business

Deeplearning4j videos

+ Add

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

Category Popularity

0-100% (relative to BigDL and Deeplearning4j)

BigDL

Deeplearning4j

Data Science And Machine Learning
23 23%
Data Science And Machine Learning
77% 77
Data Science Tools
36 36%
Data Science Tools
64% 64
Machine Learning
0 0%
Machine Learning
100% 100
Python Tools
100 100%
Python Tools
0% 0

User comments

Share your experience with using BigDL 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 should be more popular than BigDL. It has been mentiond 6 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.

BigDL mentions (1)

Deeplearning4j mentions (6)

  • DeepLearning4j Blockchain Integration: Convergence of AI, Blockchain, and Open Source Funding
    This integration is not only a technical marvel but also a case study in how open source funding and a transparent business model powered by blockchain are fostering collaboration among developers, academics, and institutional investors. With links to key resources such as the DL4J GitHub repository and the DL4J official website, the project serves as an inspiration for merging complex domains in a unified framework. - Source: dev.to / 28 days ago
  • 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 / 3 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: almost 4 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: about 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: about 4 years ago
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What are some alternatives?

When comparing BigDL and Deeplearning4j, you can also consider the following products

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.

Caffe - Caffe is an open source, deep learning framework.

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

Pylearn2 - Pylearn2 is a library for machine learning research.

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

Medium - Welcome to Medium, a place to read, write, and interact with the stories that matter most to you.

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