awesome-java
Tribuo
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awesome-java | Tribuo | |
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14 | 15 | |
39,613 | 1,220 | |
- | 1.0% | |
7.2 | 5.3 | |
15 days ago | 9 days ago | |
Java | ||
GNU General Public License v3.0 or later | Apache 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.
awesome-java
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What's the deal with Vaadin add-ons?
You, whether a web or Java expert, know the best approach. With the Vaadin add-on, you can decide and build and deliver your web components in a highly maintainable way that is best for both worlds: Ever evolving APIs and critical Java backends.
- Primeiros passos no desenvolvimento Java em 2023: um guia particular
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Do you know any frameworks that should be used with Java or javafx?
Both Awesome Java and Awesome JavaFX have very comprehensive lists of frameworks.
- Awesome Software Architecture: A curated list of useful resources about software architecture and design principles.
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Current Java Trends
There is no industry that hasn’t tried to use Java, it's everywhere: from manufacturing and medicine to games and enterprise. You can use it to automate your daily tasks or create a smart house. Check out, for example, this extensive list of different libraries and frameworks that are using Java and have become successful in the field.
- A curated list of awesome frameworks, libraries and software for the Java programming language
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Wish there was a Java lib for…
https://github.com/akullpp/awesome-java is a good start.
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If it gets better w age, will java become compatible for machine learning and data science?
Or more recently Tribuo or others.
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A Twitter bot to explore the Awesome Java list
I love making lists. I use them to organize my day, remember important things, and keep track of tools and libraries I want to explore. Lists like Awesome Java are a treat for people like me. Curated content on a technology I like and use everyday? Sign me in!
Tribuo
- FLaNK Weekly 08 Jan 2024
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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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Stochastic gradient descent written in SQL
We built model & data provenance into our open source ML library, though it's admittedly not the W3C PROV standard. There were a few gaps in it until we built an automated reproducibility system on top of it, but now it's pretty solid for all the algorithms we implement. Unfortunately some of the things we wrap (notably TensorFlow) aren't reproducible enough due to some unfixed bugs. There's an overview of the provenance system in this reprise of the JavaOne talk I gave here https://www.youtube.com/watch?v=GXOMjq2OS_c. The library is on GitHub - https://github.com/oracle/tribuo.
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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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Anybody here using Java for machine learning?
We've been developing Tribuo on Github for two years now, MS are very actively developing ONNX Runtime (and the Java layer is fairly thin and wrapped over the same C API they use for node.js and C#), and things like XGBoost and LibSVM have been around for many years and the Java bits are developed in tree with the rest of the code so updated along with it. Amazon have a team of people working on DJL, though you'd have to ask them what their plans are.
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txtai 3.4 released - Build AI-powered semantic search applications in Java
Tribuo (tribuo.org, github.com/oracle/tribuo). ONNX export support is there for 2 models at the moment in main, there's a PR for factorization machines which supports ONNX export, and we plan to add another couple of models and maybe ensembles before the upcoming release. Plus I need to write a tutorial on how it all works, but you can check the tests in the meantime.
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John Snow Labs Spark-NLP 3.1.0: Over 2600+ new models and pipelines in 200+ languages, new DistilBERT, RoBERTa, and XLM-RoBERTa transformers, support for external Transformers, and lots more!
It might be worth having a look at the ONNX Runtime Java API in addition to TF-Java, it'll let you deploy the rest of the HuggingFace pytorch models that don't have TF equivalents. I built the Java API a few years ago, and it's now a supported part of the ONNX Runtime project. We use it in Tribuo to provide one of our text feature embedding classes (BERTFeatureExtractor).
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If it gets better w age, will java become compatible for machine learning and data science?
Or more recently Tribuo or others.
The IJava notebook kernel works pretty well for data science on top of Java. We use it in Tribuo to write all our tutorials, and if you've got the jar file in the right folder everything is runnable. For example, this is our intro classification tutorial - https://github.com/oracle/tribuo/blob/main/tutorials/irises-tribuo-v4.ipynb.
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Vector API (JEP 338) Benchmark Results for Matrix Multiplication, Image Convolution, and Image Thresholding.
That sounds good. The Panama team welcome feedback. I've been using it on and off for about 4 years while it's been in development to accelerate some ML workloads (full disclosure, I work in the machine learning group in Oracle's research labs), and it's improved greatly in that time. I plan to circle back now Java 16 is out and test out vectorising Tribuo's math ops.
What are some alternatives?
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
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.
oj! Algorithms - oj! Algorithms
spark-nlp - State of the Art Natural Language Processing
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Siddhi - Stream Processing and Complex Event Processing Engine
grobid - A machine learning software for extracting information from scholarly documents
Synapses - A group of neural-network libraries for functional and mainstream languages
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
initializr - A quickstart generator for Spring projects
awesome-software-architecture - A curated list of awesome articles, videos, and other resources to learn and practice about software architecture, patterns, and principles.