Join us on this weekly Office Hours for Oracle Machine Learning on Autonomous Database, where our experts will explore exciting new features, show cool demos, and answer any questions, from simple to complex.
The Oracle Machine Learning product family supports data scientists, analysts, developers, and IT to achieve data science project goals faster while taking full advantage of the Oracle platform.
The Oracle Machine Learning Notebooks offers an easy-to-use, interactive, multi-user, collaborative interface based on Apache Zeppelin notebook technology, and support SQL, PL/SQL, Python and Markdown interpreters. It is available on all Autonomous Database versions and Tiers, including the always-free editions.
OML includes AutoML, which provides automated machine learning algorithm features for algorithm selection, feature selection and model tuning, in addition to a specialized AutoML UI exclusive to the Autonomous Database.
OML Services is also included in Autonomous Database, where you can deploy and manage native in-database OML models as well as ONNX ML models (for classification and regression) built using third-party engines, and can also invoke cognitive text analytics.
Video Highlights
00:28 Topics for the Session: OML4Py REST API
02:33 Demo on OML4Py Notebook using Autonomous Database
02:54 Build SciKit-Learn Random Forest Classifier and Store in OML Data Store
05:09 Oracle Machine Learning Random Forest model build and store
07:54 Scoring code for SciKit Learn RF model
09:34 Scoring code for OML RF model
11:51 Creating both OML4Py Scoring Functions
16:08 Store Scripts for both Scikit Learn and OML model in the OML4Py Script Repository
16:31 Check functionality of Scikit Learn Predict script and OML4Py *Apply() functions
19:29 Check functionality of OML Predict script and OML4Py *Apply() functions
21:34 Accessing predictions from REST APIs - Postman demo
21:58 REST API scoring for SciKit Learn Random Forest Classifier
23:36 REST API scoring for OML Random Forest model
25:08 Q&A
#developer #machine-learning
