Detect Anomalies in Game Transactions with ML and Sagemaker

Languages Available: Deutsch | Español (Latinoamérica) | Français | Bahasa Indonesia | Italiano | 日本語 | 한국어 | Português (Brasil) | 中文（简体) | 中文（繁體)Game studios that are building and operating multiple games tend to redo much of the server-side validation of transactional data received from game clients. This course covers the use of a central model (or multiple models per game) for offloading server processing and improving server response time. The course reviews the different anomalies associated with game transaction data and how machine learning (ML) can help perform validations.Course objectivesThis course is designed to teach you how to:Understand game transactions and associated data Recognize anomalies in game transactions Review example game report data Understand machine learning architecture for performing validationsIntended audienceThis course is intended for:Game developers Data analysts who work with game transactionsPrerequisitesWe recommend that attendees of this course have:Understanding of basic gaming concepts Basic understanding of machine learningCourse outline:Game transactions Anomalies Game report data How can ML help Demo