Algebird
Smile
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| Algebird | Smile | |
|---|---|---|
| 1 | 5 | |
| 2,147 | 5,531 | |
| 0.8% | - | |
| 7.7 | 8.5 | |
| about 2 months ago | about 1 month ago | |
| Scala | Java | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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.
Algebird
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Symbolics.jl: A Modern Computer Algebra System for a Modern Language
Hey, I have... I'm a co-author of Algebird[0], which has many ideas that I'd pull over.
I'm hoping to introduce Clojure's "spec" or "schema" libraries so that the types at play can at least be inspectable inside the system. In a fully typed language, I'd implement the extensible generics as typeclasses.
I suspect it would make it quite a bit tougher (at least in the approach I'm imagining) for folks to write new generic functions, due to many type constructors...
On the other hand, the complexity is there, even if you don't write it down!
It would be a big project, and a worthy effort, to write down types for everything in SICM.
Smile
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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.
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.
Weka
Breeze - Breeze is a numerical processing library for Scala.
grobid - A machine learning software for extracting information from scholarly documents
Apache Flink - Apache Flink
JSAT - Java Statistical Analysis Tool, a Java library for Machine Learning
Apache Mahout - Mirror of Apache Mahout
H2O - Sparkling Water provides H2O functionality inside Spark cluster
Zeppelin - Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
ND4S - ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J.