The Knowledge Base

11766 - An Oracle Database Approach to the Taxi Fare Problem 

04-13-2020 03:16 PM

Presenter Information: Jose Rodriguez, The Pythian Group (Canada)
Recording Date: Thursday, April 30, 2020 10:30 a.m. - 11:30 a.m. ET
Duration: 1 hour

The Taxi Fare prediction is a well-known problem in machine learning (ML): we have to design, train and test an ML model to predict the taxi fare a customer of the NY City cab company will pay for a ride. This is a basic example used in several ML introductory courses and also ML and artificial intelligence (AI) websites as a foundation for more advanced topics. We will see how the data was prepared, some powerful tools included in the Oracle Data Mining module for SQL*Developer, the PL/SQL code involved to create the model and, of course, some testing. All with a live demo.

Learning Objectives:

  • Understand what the taxi fare prediction machine learning problem is about.
  • Review what kind of data is involved in the problem and what is required for the data to be usable.
  • Get a glimpse of the machine learning and data analytics tools included in the Oracle Data and Analytics option.

Educational Tracks:
#DataScience, #MachineLearning, #Analytics/BI, #EmergingTechnologies, #Conference​​​

0 Favorited
3 Files
 Insufficient Privileges

OATUG members, please log in to view this resource.
Not an OATUG member? Please contact us to learn more about access to this resource. If you are interested in OATUG membership, you can learn more about our benefits or join now.

Related Entries and Links

No Related Resource entered.