Whether delivered online or onsite, instructor-led MLflow training courses utilize interactive, hands-on practice to demonstrate how to use MLflow for streamlining and managing the machine learning lifecycle.
MLflow training is offered in two formats: "online live training" and "onsite live training". Online live training (also known as "remote live training") is conducted via an interactive, remote desktop. Onsite live training can be conducted locally at customer premises in Rome or within NobleProg's corporate training centers in Rome.
NobleProg -- Your Local Training Provider
Rome
NobleProg Rome, Via Clelia Bertini Attilj 4, Rome, italy, 34D
CoworkTalenti is located in the northern part of Rome, in the Talenti–Montesacro district, just a few minutes from the ring road. It is easily accessible via Via Nomentana.
This instructor-led live training (available online or onsite) is targeted at data scientists who wish to advance beyond basic ML model building and optimize the workflows for model creation, tracking, and deployment.
By the end of this training, participants will be able to:
Install and configure MLflow along with related ML libraries and frameworks.
Appreciate the importance of trackability, reproducibility, and deployability of an ML model.
Deploy ML models to various 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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