Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales   We introduce Microsoft Machine Learning for Apache Spark (MMLSpark), an
ecosystem of enhancements that expand the Apache Spark distributed computing
library to tackle problems in Deep Learning, Micro-Service Orchestration,
Gradient Boosting, Model Interpretability, and other areas of modern
computation. Furthermore, we present a novel system called Spark Serving that
allows users to run any Apache Spark program as a distributed, sub-millisecond
latency web service backed by their existing Spark Cluster. All MMLSpark
contributions have the same API to enable simple composition across frameworks
and usage across batch, streaming, and RESTful web serving scenarios on static,
elastic, or serverless clusters. We showcase MMLSpark by creating a method for
deep object detection capable of learning without human labeled data and
demonstrate its effectiveness for Snow Leopard conservation.

3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
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The categories of this paper are: hep-th
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
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The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
13
The categories of this paper are: quant-ph
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The categories of this paper are: cond-mat
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The categories of this paper are: q-bio
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg