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

Abstract:
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​​​

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