Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On Continuous Integration / Continuous Delivery for Automated Deployment
  of Machine Learning Models using MLOps   Model deployment in machine learning has emerged as an intriguing field of
research in recent years. It is comparable to the procedure defined for
conventional software development. Continuous Integration and Continuous
Delivery (CI/CD) have been shown to smooth down software advancement and speed
up businesses when used in conjunction with development and operations
(DevOps). Using CI/CD pipelines in an application that includes Machine
Learning Operations (MLOps) components, on the other hand, has difficult
difficulties, and pioneers in the area solve them by using unique tools, which
is typically provided by cloud providers. This research provides a more
in-depth look at the machine learning lifecycle and the key distinctions
between DevOps and MLOps. In the MLOps approach, we discuss tools and
approaches for executing the CI/CD pipeline of machine learning frameworks.
Following that, we take a deep look into push and pull-based deployments in
Github Operations (GitOps). Open exploration issues are also identified and
added, which may guide future study.

17
The categories of this paper are: q-fin
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex