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Explore Our Courses
Kubeflow
35 HoursMLOps for Azure Machine Learning
14 HoursMLOps: CI/CD for Machine Learning
35 HoursKubeflow on AWS
28 HoursKubeflow on Azure
28 HoursKubeflow Fundamentals
28 HoursMLflow
21 HoursLast Updated:
Testimonials (2)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
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.