Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning with Apache SystemML   Enterprises operate large data lakes using Hadoop and Spark frameworks that
(1) run a plethora of tools to automate powerful data
preparation/transformation pipelines, (2) run on shared, large clusters to (3)
perform many different analytics tasks ranging from model preparation,
building, evaluation, and tuning for both machine learning and deep learning.
Developing machine/deep learning models on data in such shared environments is
challenging. Apache SystemML provides a unified framework for implementing
machine learning and deep learning algorithms in a variety of shared deployment
scenarios. SystemML's novel compilation approach automatically generates
runtime execution plans for machine/deep learning algorithms that are composed
of single-node and distributed runtime operations depending on data and cluster
characteristics such as data size, data sparsity, cluster size, and memory
configurations, while still exploiting the capabilities of the underlying big
data frameworks.

5
The categories of this paper are: gr-qc
17
The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
20
The categories of this paper are: acc-phys
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio