The power behind self-driving cars, real-time facial recognition, and intelligent robots is called machine learning, a subfield of artificial intelligence (AI). The first formal definition of AI came from Arthur Samuel in 1959: 'A field of study that gives computers the ability to learn without being explicitly programmed.'
Currently, machine learning not only enables computers to park our cars and win at Jeopardy, it also allows them to beat humans at chess and Go, and to learn for itself how to play new games without any instruction. This can also lead to potential applications in sales, marketing, finance, and HR that can drive better decisions and give you a competitive edge.
You Will Learn
*What machine learning is and why it should be part of your analytics toolkit
*How the most widely used algorithms work and how to apply them
*Best practices and use cases in applying machine learning techniques
*How to start applying machine learning algorithms in an automated decisioning framework
Target Audience: BI & Analytics managers and team members
Prerequisites: BI Basic Knowledge, Statistics 101