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MLOps for Azure Machine Learning
14 heuresMLOps: CI/CD for Machine Learning
35 heuresKubeflow on AWS
28 heuresKubeflow on Azure
28 heuresKubeflow on GCP
28 heuresKubeflow on IBM Cloud
28 heuresMLflow
21 heuresKubeflow
35 heuresKubeflow on OpenShift
28 heuresKubeflow Fundamentals
28 heuresLast Updated:
Nos Clients témoignent(3)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Formation - MLflow
La qualité des explications, et le nombre important de sujets abordés
Hugo SECHIER - Expleo France
Formation - Kubeflow on AWS
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.