Apache Mahout VS Smile

Compare Apache Mahout vs Smile and see what are their differences.

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Apache Mahout Smile
0 8
2,117 5,904
0.3% -
8.3 9.0
about 20 hours ago 6 days ago
HTML Java
Apache License 2.0 GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

Apache Mahout

Posts with mentions or reviews of Apache Mahout. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Apache Mahout yet.
Tracking mentions began in Dec 2020.

Smile

Posts with mentions or reviews of Smile. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-03.
  • Just want to vent a bit
    3 projects | /r/ProgrammingLanguages | 3 Dec 2022
    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.
  • Anybody here using Java for machine learning?
    11 projects | /r/java | 13 Sep 2022
    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.
  • What libraries do you use for machine learning and data visualizing in scala?
    5 projects | /r/scala | 27 Nov 2021
    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.
  • Python VS Scala
    2 projects | /r/scala | 2 Jul 2021
    Actually, it does. Scala has Spark for data science and some ML libs like Smile.
  • Machine learning on JVM
    6 projects | /r/scala | 5 Apr 2021
    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?

When comparing Apache Mahout and Smile you can also consider the following projects:

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.

H2O - Sparkling Water provides H2O functionality inside Spark cluster

Apache Flink - Apache Flink

ND4S - ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J.

tensorflow-keras-scala - Scala-based Keras API for the Java bindings to TensorFlow. Mirror of https://codeberg.org/sciss/tensorflow-keras-scala

Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java