MLOps
End to end ML Project
Project setup:
Model training:
Run: python main.py
Model... See more
Project setup:
- Open this in VSCode
- Install Dev Containers
- Do Cmd + Shift + P -> Dev Containers: Rebuild Container Without Cache
- Activate the conda virtual environment: source activate endtoend
- Inside Dev Container, run mlflow and prefect local servers: nohup bash ./start_backend.sh
Model training:
Run: python main.py
Model... See more
arghhjayy • GitHub - arghhjayy/EndToEndML: End to end ML pipeline written with open source tools exclusively
Onyxia Datalab
The modern datascience stack made accessible
Pool computing resources and provide a state of the art work environment to your data scientists without relying on big tech closed-source software.
The modern datascience stack made accessible
Pool computing resources and provide a state of the art work environment to your data scientists without relying on big tech closed-source software.
Onyxia Datalab
Ensuring availability during peak traffic by maintaining all GPU instance types could lead to prohibitively high costs. To avoid the financial strain of idle instances, we implemented a “standby instances” mechanism. Rather than preparing for the maximum potential load, we maintained a calculated number of standby instances that match the... See more