Data-Analysis: TensorFlow models

Mon, 01 Jan 0001 00:00:00 +0000

Tensorflow is a framework for creating neural networks. It implements basic linear algebra and multi-variable calculus operations in a scalable fashion, and allows users to easily chain these operations into a computation graph.

OpenText™ Analytics Database supports importing, exporting, and making predictions with TensorFlow 1.x and 2.x models trained outside of OpenText™ Analytics Database.

In-database TensorFlow integration offers several advantages:

Your models live inside your database, so you never have to move your data to make predictions.
The volume of data you can handle is limited only by the size of your database, which makes OpenText™ Analytics Database particularly well-suited for machine learning on Big Data.
OpenText™ Analytics Database offers in-database model management, so you can store as many models as you want.
Imported models are portable and can be exported for use elsewhere.

When you run a TensorFlow model to predict on data in the database, the database calls a TensorFlow process to run the model. This allows the database to support any model you can create and train using TensorFlow. OpenText™ Analytics Database just provides the inputs - your data in the database - and stores the outputs.

Data-Analysis: Using PMML models

Mon, 01 Jan 0001 00:00:00 +0000

OpenText™ Analytics Database can import, export, and make predictions with PMML models of version 4.4 and below.

OpenText Analytics Database 26.2.x – Using external models

Data-Analysis: TensorFlow models

Data-Analysis: Using PMML models