BigDL
Deep Java Library (DJL)
| BigDL | Deep Java Library (DJL) | |
|---|---|---|
| 5 | 13 | |
| 6,138 | 3,922 | |
| 2.9% | 2.1% | |
| 9.9 | 9.5 | |
| 5 days ago | 6 days ago | |
| Python | Java | |
| Apache License 2.0 | Apache License 2.0 |
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BigDL
- PyTorch Library for Running LLM on Intel CPU and GPU
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LLaMA Now Goes Faster on CPUs
Any performance benchmark against intel's 'IPEX-LLM'[0] or others?
[0] - https://github.com/intel-analytics/ipex-llm
- BigDL-LLM: running LLM on your laptop using INT4
- Fast, distributed, secure AI for Big Data
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Machine learning on JVM
Intel BigDL for Spark which again is for Spark.
Deep Java Library (DJL)
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Is deeplearning4j a good choice?
It seems to have been picked up by Eclipse and there is also Oracle Labs' Tribuo and Deep Java Library. All seem active, but I don't know much about any of them. I agree it's probably best to follow the community and use a more popular tool like PyTorch.
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Just want to vent a bit
Although it may be a bit more work, you can do both machine learning and AI in Java. If you are doing deep learning, you can use DeepJavaLibrary (I do work on this one at Amazon). If you are looking for other ML algorithms, I have seen Smile, Tribuo, or some around Spark.
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Best way to combine Python and Java?
Image preprocessing I know less about, but tokenization is something I've dealt with a bunch. There are a few options, either push the tokenizer into the ONNX model and use MS's ONNX Runtime extensions (we've used this when working with sentencepiece tokenizers), port the tokenizer entirely to Java (we did this for BERT), or use a sentencepiece or HF tokenizers wrapper directly (e.g. Amazon's DJL did this - HF, sentencepiece).
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Anybody here using Java for machine learning?
https://djl.ai/ seems very promising. I've played around with it quite a bit, not in real production though. It's a very well documented (https://d2l.djl.ai/) and active project, with Amazon working on it.
- Good document classification library in Java
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2021-09 - Plans & Hopes for Clojure Data Science
Here is link number 1 - Previous text "DJL"
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[D] Java vs Python for Machine learning
To give a contrasting perspective, I think the Java ecosystem is much better suited for many data science tasks, and has a growing and well-maintained set of libraries for general purpose machine learning. I won't list them all, but TF-Java, DJL et al. have implementations of many modern architectures and there are a number of excellent libraries (CoreNLP, Lucene et al.) for working with text.
- Does Java has similar project like this one in C#? (ml, data)
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If it gets better w age, will java become compatible for machine learning and data science?
I think DJL also use use it for their tutorials - https://docs.djl.ai/jupyter/tutorial/01_create_your_first_network.html.
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Machine learning on JVM
AWS Deep Learning more deep learning.
What are some alternatives?
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
Axle - Axle Domain Specific Language for Scientific Cloud Computing and Visualization
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Zeppelin - Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
Spire - Powerful new number types and numeric abstractions for Scala.
Tribuo - Tribuo - A Java machine learning library
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
CoreNLP - CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
PredictionIO - PredictionIO, a machine learning server for developers and ML engineers.