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 trainings in Guadalajara can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Guadalajara - Country Club Financial
Av. Prolongacion Americas 1600, Guadalajara, mexico, 44610
Situated in the prestigious Prolongacion Americas avenue and recognized as the financial district of the city, this Business centre represents a perfect corporate image in one of the most important commercial domiciles in the city. This Business centre has access to Hotels, restaurants and view to the golf course.
Guadalajara - Americas 1586
Avenue of the Americas #1586 , Guadalajara , Mexico, 44610
Spark innovative ideas in fully equipped meeting rooms and collaborate with like-minded professionals in light-filled coworking spaces. Then, ease your commute home with onsite parking, bike storage, and a choice of nearby bus and tram services, taking Achieve business excellence at Americas 1586.
Elevate your ambitions with exceptional office space located in Guadalajara’s vibrant financial hub. Work efficiently in modern, light-filled interiors behind the building’s striking mirrored-glass façade, and enjoy stunning views of the verdant fairways of Guadalajara Country Club.
Fuel innovation in fully equipped meeting rooms and connect with driven professionals in bright, collaborative coworking areas. Enjoy a hassle-free commute with convenient on-site parking, bike storage, and easy access to nearby bus and tram routes.the stress out of your journey.
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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