Online or onsite, instructor-led live MLflow training courses demonstrate through interactive hands-on practice how to use MLflow for streamlining and managing the machine learning lifecycle.
MLflow training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live MLflow training can be carried out locally on customer premises in Caracas or in NobleProg corporate training centers in Caracas.
NobleProg -- Your Local Training Provider
Caracas - Centro Lido
Av. Francisco de Miranda, Centro Lido, Torre D, Caracas, venezuela, 1060
The Center is located ten minutes from the Francisco Fajardo Highway that leads to the local airport and only two blocks from the subway station in the main financial district of Caracas.
This instructor-led, live training in (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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the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
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