This is a continuation of the series, Machine Learning With PeopleSoft. The first was an introduction, then I provided a post covering the first step in Machine Learning (ML): Data Acquisition. In this post, I will talk about the next and possibly the most important step in Machine Learning with PeopleTools 8.58: Data Modeling. Once the data is flattened and available in Elasticsearch, it can be used to train and build a Machine Learning Model.
Using the PeopleTools 8.58 Data Distribution framework, data was flattened and pushed to an Elasticsearch index. This data can be used to build and train an ML Model. We will use a new platform available on Oracle Cloud Infrastructure (OCI) called Data Science Service for this purpose. OCI Data Science service is a collaborative platform for building powerful and scalable ML Solutions. It is based on Python and other open source ML libraries & provides a platform to build, train and manage ML Models. More information on the OCI Data Science Service can be found here.
These are the steps required to build and train a ML Model using OCI Data Science Service:
1. Configure OCI tenancy to use Data Science
Oracle provides you with USD 300 cloud credits that are valid up to 30 days. [link]
The first step is to configure the OCI tenancy to use Data Science. This involves…
Details on these steps can be found in the Data Science Documentation. Once the tenancy has been configured, the Data Science platform can be accessed from – OCI Main menu -> Data and AI -> Data Science
2. Create a new Data Science Project
After configuring the tenancy, click on Data Science -> Projects to go to the Projects screen. This screen will list all the projects based on the selected compartment.