The Spotter Learning Machine
This document provides an overview of features and enhancements included in The Spotter Machine Learning. It is intended solely to help you assess the business benefits of leveraging the The Spotter data management and analytics platform with The Spotter Machine Learning to plan your data-driven data science, machine learning, and information technology projects.

Intended Audience

This technical brief is intended for executives, LOB managers, and practitioners who are looking to provide scalable machine learning capabilities to the data scientists, data analysts, data engineers, and application and dashboard developers across their enterprise.


This informations in any form, software or printed matter, contains proprietary information that is the exclusive property of The Spotter. Your access to and use of this confidential material is subject to the terms and conditions of your The Spotter software license and service agreement, which has been executed and with which you agree to comply. This document and information contained herein may not be disclosed, copied, reproduced or distributed to anyone outside The Spotter without prior written consent of The Spotter. This document is not part of your license agreement nor can it be incorporated into any contractual agreement with The Spotter or its subsidiaries or affiliates.

This document is for informational purposes only and is intended solely to assist you in planning for the implementation and upgrade of the product features described. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions.
The development, release, and timing of any features or functionality described in this document remains at the sole discretion of The Spotter. Due to the nature of the product architecture, it may not be possible to safely include all features described in this document without risking significant destabilization of the code.

What is Machine Learning?
Machine learning uses algorithms and statistical models to automatically process potentially large volume data to find hidden patterns, discover new insights, and make predictions for data-driven problems including:
• Predicting customer behaviors, identifying cross-selling and up-selling opportunities
• Anticipating customer churn, employee and student attrition
• Detecting anomalies and combating potential tax, medical or expense fraud
• Understanding hidden customer segments and understanding customer sentiment
• Identifying key factors that drive outcomes and delivering improved quality
Machine Learning, also referred to as predictive analytics or data mining, has been delivering measurable value for decades. Today, machine learning solutions are even more pervasive—being implemented and deployed across enterprises globally. As big data analytics technologies and user adoption matures and expands, machine learning use cases and integrated “intelligent” applications that push “the art of the possible” emerge every day and constantly raise the bar for user’s expectations.

The Spotter delivers the data science platform that enables data science teams to analyze data where it resides at scale—with minimal data movement. A data science platform involves more than just supporting machine learning algorithms. The Spotter converged database places machine learning and other essential technologies, such as Spatial, Graph, JSON, and blockchain, at the fingertips of data scientists in a single, secure, integrated platform, while expanding data access and sharing for data professionals. The Spotter Machine Learning is a key part of The Spotter converged and autonomous database strategy to reduce management overhead and complexity for an end-to-end optimized experience.

(TSML) empowers data scientists and data
analysts to extract knowledge, discover new insights, and make
data-driven predictions—working directly with large data volumes
in The Spotter Database, The Spotter Autonomous Database, and Big Data.
environments. (TSML) empowers application developers by making it easy to deploy and use machine learning models and solutions in applications and dashboards. In this technical brief, we introduce The Spotter Machine Learning and how it enables enterprise data science teams to achieve greater value from data.

Users have choice and flexibility in how they interact with The Spotter Machine Learning (TSML) using popular languages and plugins such as SQL, Python, R, and REST, or using interfaces such as Oracle Machine Learning Notebooks, the Oracle Data Miner user interface, and Oracle Machine Learning AutoML User Interface. In addition, OML Services supports model management and deployment with Autonomous Database from a REST interface.

The Spotter Machine Learning supports a mixture of data analytics and machine learning methodologies. For example, users may want to combine transactional data, demographic data, customer service data, and customer comments to assemble a 360-degree customer view. They may decide to perform clustering on the customers to pre-assign them to customer segments, and then, for each segment, build separate classification, regression, or anomaly detection models for better accuracy.