Žiga Vaupot's Blog

Using AutoML in Oracle Analytics Approximately one year ago, I have written a blog post Training and deploying AutoML models in Oracle Data Lakehouse . This blog post was part of my Oracle Data Lakehouse blog series, was focusing on training and deploying AutoML models in Oracle Autonomous Data Warehouse (ADW). Besides that, the post was also focusing on storing and managing data files in object storage and registering them as external tables in ADW. AutoML generated models are stored and deployed in ADW as any other OML models. If you want to use these models in Oracle Analytics you have to manually register OML model with Oracle Analytics and use it. There is a small detail regarding the location of data to be used with such a model - data has to reside in the same database where model is deployed. Not to mention, that user has to log into OML Notebooks in ADW and perform the training there. In the latest, March 2023 Update, release this is no longer needed as Oracle Analytics ...

Charlie Berger and Abi Giles-Haigh ran the hands-on lab session yesterday (11th May 2021) at Analytics and Data Oracle User Community's, AnDOUC ( https://analyticsanddatasummit.org/ ), TechCast Days, Spring Sessions with the title A Two-Step process for Detecting Fraud . I was invited to help with the HOLs alongside with Tim Vlamis and Edelweiss Kammermann .  The hands-on lab is about taking users through Oracle Machine Learning (SQL) Notebooks while using multiple use case scenarios for analysing insurance claims data and customer behavior data. Students were running the notebooks themselves to build and apply OML models inside Oracle Autonomous Database and then worked with Oracle APEX applications that leveraged OML’s insights and predictions ... So basically, what we did was: we took the Insurance Claims data set and ran 1-Class SVM algorithm, which is used for anomaly detection in order to identify suspicious claims.  For business (and any other) users we have an option ...