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Tribuo Alternatives
Similar projects and alternatives to Tribuo
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txtai
💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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server
The Triton Inference Server provides an optimized cloud and edge inferencing solution. (by triton-inference-server)
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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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.
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deeplearning4j-examples
Discontinued Deeplearning4j Examples (DL4J, DL4J Spark, DataVec) (by deeplearning4j)
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Tribuo alternative or higher similarity.
Tribuo reviews and mentions
Posts with mentions or reviews of Tribuo.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-08.
- 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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Java engineer wants to be a researcher
FWIW, Oracle actually did release a Java ML library - https://github.com/oracle/tribuo.
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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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Hottest topics for research for JAVA software engineers
You can do ML & data science in Java (full disclosure: I help run TensorFlow-Java, I maintain ONNX Runtime's Java interface, and I'm the lead developer on Oracle Labs' Java ML library Tribuo, so I'm pretty biased). It tends not to be as favoured in research, though I've published academic ML papers which used Java implementations. People do deploy ML models quite a bit in Java in industry.
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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?
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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A note from our sponsor - SaaSHub
www.saashub.com | 25 Apr 2024
Stats
Basic Tribuo repo stats
15
1,218
5.3
22 days ago
oracle/tribuo is an open source project licensed under Apache 2.0 which is not an OSI approved license.
The primary programming language of Tribuo is Java.
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