Mastering MLOps Architecture: From Code to Deployment : Manage the production cycle of continual learning ML models with MLOps
Salvato in:
| Autore principale: | Jhajj, Raman |
|---|---|
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
New Delhi :
BPB Publications
2023.
Paris : Cyberlibris |
| Accesso online: | Accès Université d'Orléans et IFPM |
| Nota: |
Couverture. https://static2.cyberlibris.com/books_upload/136pix/9789355519498.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Mastering MLOps Architecture: From Code to Deployment, Manage the production cycle of continual learning ML models with MLOps, Raman Jhajj, New Delhi, BPB Publications, 2023, 1 vol. (264 p.), 978-93-5551-949-8 |
Documenti analoghi
-
Data scientist et mlops
(Thèse et Mémoire papier)
Pulgarin Gonzalez, Juan Pablo
[s.n.], 2020 -
Engineering MLOps : Rapidly build, test, and manage production-ready machine learning life cycles at scale
(Livre numérique)
Raj, Emmanuel
Packt Publishing, 2021 -
Hands-On MLOps on Azure : Automate, secure, and scale ML workflows with the Azure ML CLI, GitHub, and LLMOps
(Livre numérique)
De, Banibrata
Packt Publishing, 2025 -
MLOps with Red Hat OpenShift : A cloud-native approach to machine learning operations
(Livre numérique)
Brigoli, Ross, et al.
Packt Publishing, 2024 -
Practical Machine Learning on Databricks : Seamlessly transition ML models and MLOps on Databricks
(Livre numérique)
Sinha, Debu
Packt Publishing, 2023