CODEWITHSUNDEEP
google-cloud-platformgoogle-cloud-dataflow
ratchet
ratchet

Reputation: 195

Data Prep preprocess to Ml Engine

Say I have code on App Engine reading Gmail attachments, parsing that it goes to Cloud Data Store, through Data Prep recipes and steps, stored back into Data Store, then predicted on by ML Engine Tensorflow model?

Reference: enter image description here

Is this all achievable through Dataflow?

EDIT 1: Is it possible to export the Data Prep steps and use them as preprocessing before an Ml Engine Tensorflow model?

Upvotes: 0

Views: 239

Answers (1)

Rodrigo C.
Rodrigo C.

Reputation: 1184

The input for a Cloud ML Engine model can be defined how you better see fit for your project. This means you can apply the preprocessing steps the way you consider fit and then send your data to the Tensorflow model.

Be sure that the format you use in your Dataprep steps is supported by the Tensorflow model. Once you apply your Dataprep recipe with all the required steps, make sure that you use an appropriate format, such as CSV. It is recommended that you store your input to a Cloud Storage bucket for better access.

I don't know how familiar you are with Cloud Dataprep, but you can try this to check how to handle all the steps that you want to include in your recipe.

Upvotes: 1

Related Questions