Deep Java Library (DJL)
winapps
Deep Java Library (DJL) | winapps | |
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13 | 292 | |
3,853 | 7,908 | |
1.6% | - | |
9.5 | 2.7 | |
3 days ago | 7 days ago | |
Java | Shell | |
Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
winapps
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What are some of your favorite Linux apps that you use
This one might be controversial, but Winapps for Linux, app that lets run apps from within a Windows KVM as if it were native on your Linux system (https://github.com/Fmstrat/winapps)
- Idk what to do 😭
- How viable is it to use a Windows Virtual Machine in Linux?
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Does Visual Studio 2022 exist on Arch Linux?
Yes but you have to run visual studios in a windows virtual machine qemu/kvm/virtmanager Then pass virtual studio window to your desktop so it runs like it is native https://github.com/Fmstrat/winapps optional Then use winapps to make a desktop and application launcher menu entry/icon
- STOP USING WINE. DARE
- Should I switch to Linux as a guitarist?
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Working/Switching seamlessly between Linux and Windows - Ideas?
There's something called winapps which works over RDP, but you better have good specs so you get good performance. I recommend using parsec with a VM if you can passthrough a seperate GPU otherwise. https://github.com/Fmstrat/winapps
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Running Windows VM in virtualized OpenSUSE = black screen
The aim of this exercise was to test run WinApps (https://github.com/Fmstrat/winapps).
- Want to use Linux, but forced to use Office 365. Any workarounds?
- Any news from the past 6 months?
What are some alternatives?
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.
wine
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
cassowary - Run Windows Applications on Linux as if they are native, Use linux applications to launch files files located in windows vm without needing to install applications on vm. With easy to use configuration GUI
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
ArchWSL - ArchLinux based WSL Distribution. Supports multiple install.
Tribuo - Tribuo - A Java machine learning library
Awesome-Linux-Software - 🐧 A list of awesome Linux softwares
CoreNLP - CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
lutris - Lutris desktop client
Apache Flink - Apache Flink
waydroid - Waydroid uses a container-based approach to boot a full Android system on a regular GNU/Linux system like Ubuntu.