Richmond

5811 Cooney Road, Richmond, Canada, V6X 3M1
Downtown core of Richmond, close to Vancouver International Airport, major Skytrain routes, shopping centers, banks and resta...

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MLflow

21 Hours
This instructor-led, live training in Richmond (online or onsite) is aimed at data scientists who wish to go beyond building ML models and optimize the ML model creation, tracking, and deployment process. By the end of this training, participants will be able to:
  • Install and configure MLflow and related ML libraries and frameworks.
  • Appreciate the importance of trackability, reproducability and deployability of an ML model
  • Deploy ML models to different public clouds, platforms, or on-premise servers.
  • Scale the ML deployment process to accommodate multiple users collaborating on a project.
  • Set up a central registry to experiment with, reproduce, and deploy ML models.
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Testimonials (2)

the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose

Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow

La qualité des explications, et le nombre important de sujets abordés

Hugo SECHIER - Expleo France
Course - Kubeflow on AWS

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MLflow Consulting
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