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Data Engineering
Join discussions on data engineering best practices, architectures, and optimization strategies within the Databricks Community. Exchange insights and solutions with fellow data engineers.
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Forum Posts

missyT
by New Contributor III
  • 1933 Views
  • 3 replies
  • 4 kudos

Resolved! AI assistant and machine Learning

I am looking to create a basic virtual assistant (AI) that implements machine learning mechanisms.I have some basic knowledge of Python and I have seen some courses on the internet (youtube in particular) that look very interesting.But for the moment...

  • 1933 Views
  • 3 replies
  • 4 kudos
Latest Reply
valeryuaba
New Contributor III
  • 4 kudos

Hey everyone!I'm clearly excited about this topic since I'm a huge fan of AI assistants and machine learning. MissyT, creating a basic virtual assistant with machine learning capabilities is an excellent idea! With your simple knowledge of Python and...

  • 4 kudos
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Maverick1
by Valued Contributor II
  • 2999 Views
  • 3 replies
  • 6 kudos

How to deploy mlflow models to sagemaker endpoints where sagemaker refers the private docker registry?

Is it possible to deploy the mlflow model to a sagemaker endpoint where the image URL is not referring to an image in ECR but the image is actually present in a private docker registry?

  • 2999 Views
  • 3 replies
  • 6 kudos
Latest Reply
Atanu
Databricks Employee
  • 6 kudos

@Saurabh Verma​ , this to create the endpoint.also, check this out - https://github.com/mlflow/mlflow/blob/0fa849ad75e5733bf76cc14a4455657c5c32f107/mlflow/sagemaker/__init__.py#L361

  • 6 kudos
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Maverick1
by Valued Contributor II
  • 3937 Views
  • 5 replies
  • 6 kudos

How to infer the online feature store table via an mlflow registered model, which is deployed to a sagemaker endpoint?

Can an mlflow registered model automatically infer the online feature store table, if that model is trained and logged via a databricks feature store table and the table is pushed to an online feature store (like AWS RDS)?

  • 3937 Views
  • 5 replies
  • 6 kudos
Latest Reply
Atanu
Databricks Employee
  • 6 kudos

@Saurabh Verma​  let us know if you need further help on this! Thanks.

  • 6 kudos
4 More Replies
Dunken
by New Contributor III
  • 3824 Views
  • 7 replies
  • 3 kudos

Resolved! Databricks and CD4ML

I would like to use Databricks in a CD4ML way (see also https://martinfowler.com/articles/cd4ml.html). Is this possible? I would like to develop and train models in one environment once qualified, I would like to deploy the model with the application...

  • 3824 Views
  • 7 replies
  • 3 kudos
Latest Reply
Atanu
Databricks Employee
  • 3 kudos

something below you are looking for @Armin Galliker​ ?

  • 3 kudos
6 More Replies
adnanzak
by New Contributor II
  • 2702 Views
  • 3 replies
  • 0 kudos

Resolved! Deploy Databricks Machine Learing Models On Power BI

Hi Guys. I've implemented a Machine Learning model on Databricks and have registered it with a Model URL. I wanted to enquire if I could use this model on Power BI. Basically the model predicts industries based on client demographics. Ideally I would...

  • 2702 Views
  • 3 replies
  • 0 kudos
Latest Reply
adnanzak
New Contributor II
  • 0 kudos

Thank you @Werner Stinckens​  and @Joseph Kambourakis​  for your replies.

  • 0 kudos
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Maverick1
by Valued Contributor II
  • 22865 Views
  • 9 replies
  • 7 kudos

Resolved! How to deploy a databricks managed workspace model to sagemaker from databricks notebook

I wanted to deploy a registered model present in databricks managed MLFlow to a sagemaker via databricks notebook?As of now, it is not able to run mlflow sagemaker build-and-push container command directly. What all configurations or steps needed to ...

  • 22865 Views
  • 9 replies
  • 7 kudos
Latest Reply
User16871418122
Contributor III
  • 7 kudos

@Saurabh Verma​ Please try!import mlflow.sagemaker as mfs sys.stdout.fileno = lambda: 0 mfs.run_local(model_uri=model_uri,port=8000,image="test")

  • 7 kudos
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Maverick1
by Valued Contributor II
  • 4240 Views
  • 8 replies
  • 14 kudos

Resolved! Real-time model serving and monitoring on Databricks at scale

How to deploy real-time model on databricks at scale? Right now, The model serving is very limited to 20 requests per second. Also, There are no model monitoring framework/graphs like the one's provided with AzureML or Sagemaker frameworks.

  • 4240 Views
  • 8 replies
  • 14 kudos
Latest Reply
sean_owen
Databricks Employee
  • 14 kudos

I believe the next update to serving will include 1, not 2 (this is still within a Databricks workspace in a region). I don't think multi-model endpoints are on the roadmap next.How does Airflow integration relate?

  • 14 kudos
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