Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Data Quality-Driven View of MLOps   Developing machine learning models can be seen as a process similar to the
one established for traditional software development. A key difference between
the two lies in the strong dependency between the quality of a machine learning
model and the quality of the data used to train or perform evaluations. In this
work, we demonstrate how different aspects of data quality propagate through
various stages of machine learning development. By performing a joint analysis
of the impact of well-known data quality dimensions and the downstream machine
learning process, we show that different components of a typical MLOps pipeline
can be efficiently designed, providing both a technical and theoretical
perspective.

10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
22
The categories of this paper are: chao-dyn
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga