Smile
BigDL
| Smile | BigDL | |
|---|---|---|
| 9 | 5 | |
| 5,924 | 5,957 | |
| - | 19.8% | |
| 9.8 | 9.9 | |
| 5 days ago | 3 days ago | |
| Java | Python | |
| GNU General Public License v3.0 or later | 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.
Smile
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The Current State of Clojure's Machine Learning Ecosystem
> I don't think it's right to recommend that new users move away from the package because of licensing issues
I was going to chime in to agree but then I saw how this was done - a completely innocuous looking commit:
https://github.com/haifengl/smile/commit/6f22097b233a3436519...
And literally no mention in the release notes:
https://github.com/haifengl/smile/releases/tag/v3.0.0
I think if you are going to change license especially in a way that makes it less permissive you need to be super open and clear about both the fact you are doing it and your reasons for that. This is done so silently as to look like it is intentionally trying to mislead and trick people.
So maybe I wouldn't say to move away because of the specific license, but it's legitimate to avoid something when it's so clearly driven by a single entity and that entity acts in a way that isn't trustworthy.
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Need statistic test library for Spark Scala
Check out Smile too.
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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?
For deploying a trained model there are a bunch of options that use Java on top of some native runtime like TF-Java (which I co-lead), ONNX Runtime, pytorch has inference for TorchScript models. Training deep learning models is harder, though you can do it for some of them in DJL. Training more standard ML models is much simpler, either via Tribuo, or using things like LibSVM & XGBoost directly, or other libraries like SMILE or WEKA.
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What libraries do you use for machine learning and data visualizing in scala?
I use smile https://github.com/haifengl/smile with ammonite and it feels pretty easy/good to work with. Of course for pure looking at data, and exploration, you're not going to beat python.
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Python VS Scala
Actually, it does. Scala has Spark for data science and some ML libs like Smile.
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[R] NLP Machine Learning with low RAM
I guess I must have a mistake somewhere. It's not much code. it's written in Kotlin with smile. My dataset is only about 32MB. I load the dataset into memory. I then use 80% of the data for training, and the other for later testing. I get just the columns I need and store them in the variable dataset.
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Kotlin with Randon Forest Classifier
I've heard good things about Smile, probably beats libs like Weka by far. I'm not sure if you can load a scikit-learn model though, so you might need to retrain the model in Kotlin.
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Machine learning on JVM
I was using Smile for some period - https://haifengl.github.io/ - it's quite small and lightweight Java lib with some very basic algorithms - I was using in particularly cauterization. Along with this it provides Scala API.
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.
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.
Zeppelin - Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Weka
Axle - Axle Domain Specific Language for Scientific Cloud Computing and Visualization
Breeze - Breeze is a numerical processing library for Scala.
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
Apache Flink - Apache Flink
Spire - Powerful new number types and numeric abstractions for Scala.
ND4S - ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J.
PredictionIO - PredictionIO, a machine learning server for developers and ML engineers.