Publicação
Towards MLOps in a Startup Company
| Resumo: | Companies which have developed around a product or service built on top of one or several machine learning applications will reach a point where the complexity of these applications become unfeasible to manage manually. To approach a more mature level of their machine learning applications these companies must start implementing MLOps in their operations as well as orchestration tooling for building durable and scalable machine learning pipelines. This paper presents how a startup company in the marketing- and market research sector has taken their first steps towards machine learning maturity by implementing MLOps practices and orchestration with Apache Airflow. |
|---|---|
| Autores principais: | Ene, Emil Henricsson |
| Assunto: | MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1866811148508069888 |
|---|---|
| author | Ene, Emil Henricsson |
| author_facet | Ene, Emil Henricsson |
| author_role | author |
| contributor_name_str_mv | Bastos, João Roto, Ville Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Ene, Emil Henricsson\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Bastos, João Roto, Ville Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Ene, Emil Henricsson |
| datacite.date.Accepted.fl_str_mv | 2023-03-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-05-22T12:25:04Z |
| datacite.date.embargoed.fl_str_mv | 2023-05-22T12:25:04Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| datacite.titles.title.fl_str_mv | Towards MLOps in a Startup Company |
| dc.contributor.none.fl_str_mv | Bastos, João Roto, Ville Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Ene, Emil Henricsson |
| dc.date.Accepted.fl_str_mv | 2023-03-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-05-22T12:25:04Z |
| dc.date.embargoed.fl_str_mv | 2023-05-22T12:25:04Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.5/27794 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Instituto Superior de Economia e Gestão |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| dc.title.fl_str_mv | Towards MLOps in a Startup Company |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | Companies which have developed around a product or service built on top of one or several machine learning applications will reach a point where the complexity of these applications become unfeasible to manage manually. To approach a more mature level of their machine learning applications these companies must start implementing MLOps in their operations as well as orchestration tooling for building durable and scalable machine learning pipelines. This paper presents how a startup company in the marketing- and market research sector has taken their first steps towards machine learning maturity by implementing MLOps practices and orchestration with Apache Airflow. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/ef6dd629-f146-485c-8183-ab0ab2c77dac/download |
| id | ul_74a71b3dbcb8eb33dad8a8826c101f8d |
| identifier.url.fl_str_mv | http://hdl.handle.net/10400.5/27794 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10400.5/27794 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Ene, Emil Henricsson |
| publishDate | 2023 |
| publisher.none.fl_str_mv | Instituto Superior de Economia e Gestão |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engInstituto Superior de Economia e Gestãopt_PTCompanies which have developed around a product or service built on top of one or several machine learning applications will reach a point where the complexity of these applications become unfeasible to manage manually. To approach a more mature level of their machine learning applications these companies must start implementing MLOps in their operations as well as orchestration tooling for building durable and scalable machine learning pipelines. This paper presents how a startup company in the marketing- and market research sector has taken their first steps towards machine learning maturity by implementing MLOps practices and orchestration with Apache Airflow.application/pdfpt_PTTowards MLOps in a Startup CompanyEne, Emil HenricssonBastos, JoãoRoto, VilleHostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.pt2023-05-22T12:25:04Z2023-032023-03-01T00:00:00ZHandlehttp://hdl.handle.net/10400.5/27794http://purl.org/coar/access_right/c_abf2open accessMLOpsAutomationMachine Learning PipelinesOrchestrationApache AirflowDAGsParallelization907970 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/ef6dd629-f146-485c-8183-ab0ab2c77dac/download |
| spellingShingle | Towards MLOps in a Startup Company Ene, Emil Henricsson MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| status | SINGLETON |
| subject.fl_str_mv | MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| title | Towards MLOps in a Startup Company |
| title_full | Towards MLOps in a Startup Company |
| title_fullStr | Towards MLOps in a Startup Company |
| title_full_unstemmed | Towards MLOps in a Startup Company |
| title_short | Towards MLOps in a Startup Company |
| title_sort | Towards MLOps in a Startup Company |
| topic | MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| topic_facet | MLOps Automation Machine Learning Pipelines Orchestration Apache Airflow DAGs Parallelization |
| url | http://hdl.handle.net/10400.5/27794 |
| visible | 1 |