Coveo Machine Learning

Coveo Machine Learning

Learn and master the core principles and mechanics of Coveo Machine Learning. Go in-depth into machine learning models and significantly improve relevance across channels for every audience.

About this course

This course will provide you with in-depth information on how to set-up, maintain and analyze Coveo Machine Learning models to create relevant experiences for your audiences. 

Learn the core principles, mechanics and models you need to master in order to fully leverage all Coveo Machine Learning features across Coveo platform use cases.

Element covered include:

  • How to explain the fundamental concepts behind the Machine Learning
  • How Coveo Machine Learning Model improves relevance
  • Data used by Coveo Machine Learning and how it is used by each Models
  • Configuring a Coveo Machine Learning Model Training Phase
  • The role of Filter Context and User Context in Coveo Machine Learning
  • Configuring a Query Suggest Model and evaluate its key performance measures
  • Configuring an Automatic Relevance Tuning Model and evaluate its key performance measures

 

 

 

Curriculum2 hrs 55 min

  • Introduction to Machine Learning
  • Preview
    1.0 Introduction 0 hrs 3 min
  • 1.1 Learning Objectives 0 hrs 0 min
  • 1.2 AI and Machine Learning 0 hrs 5 min
  • 1.3 Core Insight 0 hrs 1 min
  • 1.4 What Powers It 0 hrs 1 min
  • 1.5 How It Learns 0 hrs 2 min
  • 1.6 How It Improves 0 hrs 3 min
  • 1.7 How It Generates More Relevant Predictions 0 hrs 3 min
  • 1.8 In Summary 0 hrs 1 min
  • 1.9 Quiz 0 hrs 5 min
  • Coveo Machine Learning Models
  • 2.1 Learning Objectives 0 hrs 1 min
  • 2.2 Query Suggest 0 hrs 2 min
  • 2.3 Automatic Relevance Tuning 0 hrs 2 min
  • 2.4 Intelligent Term Detection 0 hrs 2 min
  • 2.5 Recommendation 0 hrs 3 min
  • 2.6 All Four Models 0 hrs 1 min
  • 2.7 Quiz
  • Coveo Machine Learning Data
  • 3.1 Learning Objectives 0 hrs 1 min
  • 3.2 Usage Analytics Events Classification 0 hrs 3 min
  • 3.3 Cause, Type and Value 0 hrs 5 min
  • 3.4 DEMO - Viewing and Analyzing UA Events 0 hrs 1 min
  • 3.5 Assessing Your Integration 0 hrs 1 min
  • 3.6 Quiz 0 hrs 5 min
  • Coveo Machine Learning - Model Building
  • 4.1 Learning Objectives 0 hrs 1 min
  • 4.2 Big Picture 0 hrs 3 min
  • 4.3 The Basics 0 hrs 4 min
  • 4.4 Training Phase Overview 0 hrs 3 min
  • 4.5 DEMO - How to Create a Model 0 hrs 2 min
  • 4.6 Train on Events 0 hrs 1 min
  • 4.7 Quiz 0 hrs 5 min
  • Coveo Machine Learning Context
  • 5.1 Learning Objectives 0 hrs 2 min
  • 5.2 DEMO - Model Panel 0 hrs 1 min
  • 5.3 Defining Context 0 hrs 5 min
  • 5.4 Filter Context 0 hrs 6 min
  • 5.5 Training and Prediction Phase 0 hrs 3 min
  • 5.6 DEMO - Finding the Context on Queries and Events 0 hrs 4 min
  • 5.7 User Context 0 hrs 3 min
  • 5.8 Quiz 0 hrs 5 min
  • Query Suggest
  • 6.1 Learning Objectives 0 hrs 2 min
  • 6.2 How It Learns 0 hrs 3 min
  • 6.3 How It Predicts 0 hrs 1 min
  • 6.4 And Thesaurus 0 hrs 3 min
  • 6.5 DEMO - Creating and Evaluating a Query Suggest Model 0 hrs 3 min
  • 6.6 Key Performance Measures 0 hrs 1 min
  • 6.7 DEMO - Query Suggest and Usage Analytics 0 hrs 3 min
  • 6.8 Quiz 0 hrs 5 min
  • Automatic Relevance Tuning
  • 7.1 Learning Objectives 0 hrs 1 min
  • 7.2 Big Picture 0 hrs 2 min
  • 7.3 How It Learns 0 hrs 4 min
  • 7.4 Model Panel 0 hrs 1 min
  • 7.5 DEMO - Creating and Evaluating an Automatic Relevance Tuning Model - Part 1 0 hrs 2 min
  • 7.6 DEMO - Creating and Evaluating an Automatic Relevance Tuning Model - Part 2 0 hrs 3 min
  • 7.7 How It Predicts 0 hrs 1 min
  • 7.8 DEMO - Automatic Relevance Tuning and Impact on Relevancy 0 hrs 3 min
  • 7.9 Options 0 hrs 5 min
  • 7.10 DEMO - Deploying and Testing an ART Model 0 hrs 4 min
  • 7.11 Key Performance Measures 0 hrs 1 min
  • 7.12 DEMO - Automatic Relevance Tuning and Usages Analytics 0 hrs 4 min
  • 7.13 Quiz 0 hrs 5 min
  • To learn more ...

About this course

This course will provide you with in-depth information on how to set-up, maintain and analyze Coveo Machine Learning models to create relevant experiences for your audiences. 

Learn the core principles, mechanics and models you need to master in order to fully leverage all Coveo Machine Learning features across Coveo platform use cases.

Element covered include:

  • How to explain the fundamental concepts behind the Machine Learning
  • How Coveo Machine Learning Model improves relevance
  • Data used by Coveo Machine Learning and how it is used by each Models
  • Configuring a Coveo Machine Learning Model Training Phase
  • The role of Filter Context and User Context in Coveo Machine Learning
  • Configuring a Query Suggest Model and evaluate its key performance measures
  • Configuring an Automatic Relevance Tuning Model and evaluate its key performance measures

 

 

 

Curriculum2 hrs 55 min

  • Introduction to Machine Learning
  • Preview
    1.0 Introduction 0 hrs 3 min
  • 1.1 Learning Objectives 0 hrs 0 min
  • 1.2 AI and Machine Learning 0 hrs 5 min
  • 1.3 Core Insight 0 hrs 1 min
  • 1.4 What Powers It 0 hrs 1 min
  • 1.5 How It Learns 0 hrs 2 min
  • 1.6 How It Improves 0 hrs 3 min
  • 1.7 How It Generates More Relevant Predictions 0 hrs 3 min
  • 1.8 In Summary 0 hrs 1 min
  • 1.9 Quiz 0 hrs 5 min
  • Coveo Machine Learning Models
  • 2.1 Learning Objectives 0 hrs 1 min
  • 2.2 Query Suggest 0 hrs 2 min
  • 2.3 Automatic Relevance Tuning 0 hrs 2 min
  • 2.4 Intelligent Term Detection 0 hrs 2 min
  • 2.5 Recommendation 0 hrs 3 min
  • 2.6 All Four Models 0 hrs 1 min
  • 2.7 Quiz
  • Coveo Machine Learning Data
  • 3.1 Learning Objectives 0 hrs 1 min
  • 3.2 Usage Analytics Events Classification 0 hrs 3 min
  • 3.3 Cause, Type and Value 0 hrs 5 min
  • 3.4 DEMO - Viewing and Analyzing UA Events 0 hrs 1 min
  • 3.5 Assessing Your Integration 0 hrs 1 min
  • 3.6 Quiz 0 hrs 5 min
  • Coveo Machine Learning - Model Building
  • 4.1 Learning Objectives 0 hrs 1 min
  • 4.2 Big Picture 0 hrs 3 min
  • 4.3 The Basics 0 hrs 4 min
  • 4.4 Training Phase Overview 0 hrs 3 min
  • 4.5 DEMO - How to Create a Model 0 hrs 2 min
  • 4.6 Train on Events 0 hrs 1 min
  • 4.7 Quiz 0 hrs 5 min
  • Coveo Machine Learning Context
  • 5.1 Learning Objectives 0 hrs 2 min
  • 5.2 DEMO - Model Panel 0 hrs 1 min
  • 5.3 Defining Context 0 hrs 5 min
  • 5.4 Filter Context 0 hrs 6 min
  • 5.5 Training and Prediction Phase 0 hrs 3 min
  • 5.6 DEMO - Finding the Context on Queries and Events 0 hrs 4 min
  • 5.7 User Context 0 hrs 3 min
  • 5.8 Quiz 0 hrs 5 min
  • Query Suggest
  • 6.1 Learning Objectives 0 hrs 2 min
  • 6.2 How It Learns 0 hrs 3 min
  • 6.3 How It Predicts 0 hrs 1 min
  • 6.4 And Thesaurus 0 hrs 3 min
  • 6.5 DEMO - Creating and Evaluating a Query Suggest Model 0 hrs 3 min
  • 6.6 Key Performance Measures 0 hrs 1 min
  • 6.7 DEMO - Query Suggest and Usage Analytics 0 hrs 3 min
  • 6.8 Quiz 0 hrs 5 min
  • Automatic Relevance Tuning
  • 7.1 Learning Objectives 0 hrs 1 min
  • 7.2 Big Picture 0 hrs 2 min
  • 7.3 How It Learns 0 hrs 4 min
  • 7.4 Model Panel 0 hrs 1 min
  • 7.5 DEMO - Creating and Evaluating an Automatic Relevance Tuning Model - Part 1 0 hrs 2 min
  • 7.6 DEMO - Creating and Evaluating an Automatic Relevance Tuning Model - Part 2 0 hrs 3 min
  • 7.7 How It Predicts 0 hrs 1 min
  • 7.8 DEMO - Automatic Relevance Tuning and Impact on Relevancy 0 hrs 3 min
  • 7.9 Options 0 hrs 5 min
  • 7.10 DEMO - Deploying and Testing an ART Model 0 hrs 4 min
  • 7.11 Key Performance Measures 0 hrs 1 min
  • 7.12 DEMO - Automatic Relevance Tuning and Usages Analytics 0 hrs 4 min
  • 7.13 Quiz 0 hrs 5 min
  • To learn more ...