Deploy machine learning inference graph on Kubernetes Seldon
$210
Delivery in
2 days
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What you get with this Offer
Deploy and scale your serving machine learning model as a microservice on Kubernetes. In this offer we will package your machine learning inference graph using Seldon Framework.
This offer covers the followings:
1. Constructing prediction class in Python.
2. Building the docker image.
3. Creating Kubernetes Seldon Resource Deployment manifest.
4. Jupyter notebook to test the deployment on Kubernetes.
5. README.md file that documents the build and deploy commands.
This offer covers one component of the inference graph.
If you would like to automate this process, we would be happy to create a full CICD pipeline on GitLab.
This offer covers the followings:
1. Constructing prediction class in Python.
2. Building the docker image.
3. Creating Kubernetes Seldon Resource Deployment manifest.
4. Jupyter notebook to test the deployment on Kubernetes.
5. README.md file that documents the build and deploy commands.
This offer covers one component of the inference graph.
If you would like to automate this process, we would be happy to create a full CICD pipeline on GitLab.
Get more with Offer Add-ons
-
I can add extra microservice in the inference graph
Additional 1 working day
+$75 -
I can create CICD pipeline on GitLab
Additional 1 working day
+$100
What the Freelancer needs to start the work
We need to get started:
1. A diagram of the pipeline.
2. The names of models inputs and outputs tensors.
3. Any input/output data transformation code you want to include.
4. A list of prerequisite packages.
5. Access to the model registry.
6. Access to your docker registry.
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