Welcome to this Db2 lab that highlights some of the new ways to access Db2 through REST services and build Machine Learning models for and with Db2. This lab uses Jupyter notebooks to demonstrate these features. If you are not familiar with the use of Jupyter notebooks or Python, the following notebooks will guide you through their usage. You can find a copy of these notebooks at https://github.com/Db2-DTE-POC/modernization.
The Hands-on Lab Includes the following modules:
If you are not familiar with the use of Jupyter notebooks or Python, the following notebook will guide you through their usage. Db2 Magic Commands
Db2 Magic commands are used in all of the notebooks used in this lab. The following notebook provides a tutorial on basics of using the Db2 magic commands.
10 min
The IBM Db2 Data Management Console builds on the best of Data Server Manager to help you manage one to hundreds of databases across the Db2 family from ground to cloud. Everything you can do through the user interface is also available through RESTful services calls. The Hands-on Lab walks you through sample code to interact with the console using REST and Python for object exploration, monitoring as well as the setup, configuration and management of the console itself.
90 min
This lab contains an example of how to develop a customer segmentation machine learning model with Db2's native machine learning functionality.
90 min
This lab contains an example of how to develop a machine learning pipeline externally in a Jupyter notebook and deploy the pipeline to Db2 for in-database scoring with Python UDFs.
90 min
You can extend your Db2 system so that application programmers can create Representational State Transfer (REST) endpoints to interact with your Db2 database. The Hands-on Lab includes a reusable Python class library to make using the RESTful endpoint services easy and fast for experienced or novice Python programmers.
40 min