Deeplearning4j
Smile
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Deeplearning4j | Smile | |
---|---|---|
13 | 9 | |
13,424 | 5,924 | |
0.5% | - | |
6.5 | 9.8 | |
8 days ago | about 3 hours ago | |
Java | 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.
Deeplearning4j
- Deeplearning4j Suite Overview
- Java for ML?
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Best way to combine Python and Java?
Have you considered migrating off of Python to just using JVM ML libraries then? I hear good things about Deeplearning4j, but there's quite a few.
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Anybody here using Java for machine learning?
I've gone to the linux workflow as directed in the docs and reconstructed the maven command line:
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Data Science Competition
DL4J
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Java Matrix Benchmark is Updated! See how linear algebra libraries compare for speed
Hey folks, just letting you know we see this thread and I appreciate you guys running these benchmarks. I'm not seeing any of your posts on our forums. I think I saw a notification from our examples but we do not actually monitor that. Please use: https://community.konduit.ai/ or at least the main repo dl4j issues: https://github.com/eclipse/deeplearning4j/issues and you'll get a lot more visibility. Thanks!
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Does Java has similar project like this one in C#? (ml, data)
Also, the website is now redirected to: https://deeplearning4j.konduit.ai/
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If it gets better w age, will java become compatible for machine learning and data science?
On top of this several popular projects have been built. This includes tensorflow-java and our project eclipse deeplearning4j: https://github.com/eclipse/deeplearning4j
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Matrices multiplication benchmark: Apache math vs colt vs ejml vs la4j vs nd4j
Nd4j is actively developed. The latest commit was 6 hours ago. Nd4j is part of deeplearning4j which is now owned by eclipse (but the main contributors are from a company) https://github.com/eclipse/deeplearning4j/tree/master/nd4j
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.
What are some alternatives?
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
Weka
tensorflow - An Open Source Machine Learning Framework for Everyone
Breeze - Breeze is a numerical processing library for Scala.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Apache Flink - Apache Flink
Apache Mahout - Mirror of Apache Mahout
ND4S - ND4S: N-Dimensional Arrays for Scala. Scientific Computing a la Numpy. Based on ND4J.
H2O - Sparkling Water provides H2O functionality inside Spark cluster