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why not write the ML model in Java?

imagiko 7y ago
One way is to obviously go all out Java - definitely makes things streamlined. But not all team members are familiar with Java. Especially not ones formally trained on data science - who tend to work with R/python etc. Atleast that has been my experience.
smabie 7y ago
The better question, is why Java? I don’t think I’ve ever encountered any company or person to use Java for ML. Scala yes. Clojure, surprisingly, yes. Java, no. Not to say they don’t exist, but it’s not a good idea. The ecosystem isn’t there, and the language (I want to say sucks), isn’t there either.
- abc_lisper 7y ago
  Where did you see clojure being used in production for ML? I am curious, because I am a clojure dev
  - ohnoforgotid 7y ago
    https://www.infoq.com/presentations/Why-Prismatic-Goes-Faster-With-Clojure/ https://www.infoq.com/presentations/Why-Prismatic-Goes-Faste...
  - thom 7y ago
    We have used clj-ml[0], which wraps a bunch of Weka stuff, as well as the XGBoost JVM bindings. I've used Bayadera[1] and Dragan's other tools for linear algebra, although not in production. I was always sad that Incanter didn't really go anywhere, but at this point I wouldn't be surprised if Clojure became a respectable platform for data science, especially given Clojurists Together's funding focus this quarter[2]. 0: https://github.com/shark8me/clj-ml https://github.com/shark8me/clj-ml 1: https://github.com/uncomplicate/bayadera https://github.com/uncomplicate/bayadera 2: https://www.clojuriststogether.org/news/q4-2019-funding-announcement/ https://www.clojuriststogether.org/news/q4-2019-funding-anno...
m00x 7y ago
Because all of the large tools are in Python. Tensorflow, PyTorch, OpenCV, Numpy, Pandas, etc.
- itronitron 7y ago
  The OP mentions that they are currently working in R.
wmeddie 7y ago
As someone slightly involved in the Deeplearning4J[1] project it always surprises me that more people don't consider this option. [1]: https://github.com/eclipse/deeplearning4j https://github.com/eclipse/deeplearning4j

One way is to obviously go all out Java - definitely makes things streamlined. But not all team members are familiar with Java. Especially not ones formally trained on data science - who tend to work with R/python etc. Atleast that has been my experience.

smabie 7y ago

The better question, is why Java? I don’t think I’ve ever encountered any company or person to use Java for ML. Scala yes. Clojure, surprisingly, yes. Java, no. Not to say they don’t exist, but it’s not a good idea. The ecosystem isn’t there, and the language (I want to say sucks), isn’t there either.

abc_lisper 7y ago
Where did you see clojure being used in production for ML? I am curious, because I am a clojure dev
- ohnoforgotid 7y ago
  https://www.infoq.com/presentations/Why-Prismatic-Goes-Faster-With-Clojure/ https://www.infoq.com/presentations/Why-Prismatic-Goes-Faste...
- thom 7y ago
  We have used clj-ml[0], which wraps a bunch of Weka stuff, as well as the XGBoost JVM bindings. I've used Bayadera[1] and Dragan's other tools for linear algebra, although not in production. I was always sad that Incanter didn't really go anywhere, but at this point I wouldn't be surprised if Clojure became a respectable platform for data science, especially given Clojurists Together's funding focus this quarter[2]. 0: https://github.com/shark8me/clj-ml https://github.com/shark8me/clj-ml 1: https://github.com/uncomplicate/bayadera https://github.com/uncomplicate/bayadera 2: https://www.clojuriststogether.org/news/q4-2019-funding-announcement/ https://www.clojuriststogether.org/news/q4-2019-funding-anno...

m00x 7y ago

Because all of the large tools are in Python. Tensorflow, PyTorch, OpenCV, Numpy, Pandas, etc.

itronitron 7y ago
The OP mentions that they are currently working in R.

wmeddie 7y ago

As someone slightly involved in the Deeplearning4J[1] project it always surprises me that more people don't consider this option. [1]: https://github.com/eclipse/deeplearning4j https://github.com/eclipse/deeplearning4j