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Cool, this is a helpful intro. Anyone have any recommended reading for ML in a JVM context?

• marcinzm 10y ago
  If you're interested in the big data side of things there's Spark (http://spark.apache.org/ http://spark.apache.org/) and MLlib for it (http://spark.apache.org/docs/latest/ml-guide.html http://spark.apache.org/docs/latest/ml-guide.html). H20 (http://www.h2o.ai/ http://www.h2o.ai/) also provides ML algorithms on top of Spark (and I think independent of Spark as well, not sure of the current status). These are all written on the JVM either in Scala (Spark) or Java (H20).
• adamnemecek 10y ago
  I haven't read it but this book looks reasonable https://www.amazon.com/Scala-Machine-Learning-Patrick-Nicolas/dp/1783558741/ https://www.amazon.com/Scala-Machine-Learning-Patrick-Nicola...
• esfandia 10y ago
  Weka is a popular machine learning toolkit in Java: http://www.cs.waikato.ac.nz/ml/weka/ http://www.cs.waikato.ac.nz/ml/weka/ and they have a textbook to go with it: http://www.cs.waikato.ac.nz/ml/weka/book.html http://www.cs.waikato.ac.nz/ml/weka/book.html as well as an online course: https://weka.waikato.ac.nz/dataminingwithweka/preview https://weka.waikato.ac.nz/dataminingwithweka/preview
• otoburb 10y ago
  The Skymind.io co-founders wrote a book that references their open-source "deep learning for Java and Scala framework"[1]. They are in the YC16 batch. [1] https://deeplearning4j.org/about https://deeplearning4j.org/about
• agibsonccc 10y ago
  Hi, skymind cofounder here. To offer some context on our book there: We have appendixes covering some of the fundamental concepts such as linear algebra and statistics. For other machine learning libraries in java: https://github.com/haifengl/smile https://github.com/haifengl/smile http://knime.org http://knime.org http://rapidminer.com http://rapidminer.com