This class will provide you with in-depth information on how to set-up, maintain and analyze Coveo Machine Learning models to significantly improve relevance and success with your Coveo user experience.
By taking this course, you will learn:
Description: In this mandatory step, you will explore the concepts and elements that the Coveo Platform uses to power a Machine Learning driven search experience. This includes Query Parameters, Usage Analytics Events and Dimensions, Context, Query Pipelines and more.
Description: In this section, you will learn about the mechanics through which the Machine Learning features can optimize the experience for your Visitors. You will explore concepts like: how does it learn, what are the key things to know about each model, what type of information should be used to develop the models and more.
Description: In this section, you will learn the 4 axis of design when building a Machine Learning driven search experience. You will learn how to clearly define your target audiences in terms that can be leverage to create a Machine Learning driven experience and how to configure your Search Interface to measure your audience behavior and utilization of Machine Learning.
Description: In this final section, you will put everything you have learned so far into practice by studying 3 archetypical Machine Learning driven search experiences. We will show how the design principles are applied in the context of:
- A Search Portal
- A agent Panel
- An E-commerce portal
Description: In this section, we will cover the basics of Machine Learning instrumentation in the context of providing relevance. We will analyze a business use case example and discuss the importance of dimensions, custom events and context to make Machine Learning successful.