The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
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The Power of Machine Learning: Boost Business, Accumulate Clicks, Fight Fraud, and Deny Deadbeats
Duration: 10 hours
EBES1 : EBES1
This course will prepare you to participate in the deployment of machine learning – whether you'll do so in the role of enterprise leader or quant. In order to serve both types, this course goes further than typical machine learning courses, which cover only the technical foundations and core quantitative techniques. This curriculum uniquely integrates both sides – both the business and tech know-how – that are essential for deploying machine learning.
Learn How To
  • How launching machine learning – aka predictive analytics – improves marketing, financial services, fraud detection, and many other business operations
  • A concrete yet accessible guide to predictive modeling methods, delving most deeply into decision trees
  • Reporting on the predictive performance of machine learning and the profit it generates
  • What your data needs to look like before applying machine learning
  • Avoiding the hype and false promises of “artificial intelligence”
  • AI ethics: social justice concerns, such as when predictive models blatantly discriminate by protected class
  • Course Outline
    Power of Machine Learning
  • How launching machine learning – aka predictive analytics – improves marketing, financial services, fraud detection, and many other business operations
  • A concrete yet accessible guide to predictive modeling methods, delving most deeply into decision trees
  • Reporting on the predictive performance of machine learning and the profit it generates
  • What your data needs to look like before applying machine learning
  • Avoiding the hype and false promises of “artificial intelligence”
  • AI ethics: social justice concerns, such as when predictive models blatantly discriminate by protected class
  • THIS COURSE IS PART OF

    SAS Statistics Foundations​ Learning Subscription



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