Lucidworks Fusion AI

Paris
June 26, 2019
12:00 - 12:00am

Course Overview

Lucidworks’ Fusion AI training is the right choice for those interested in taking Fusion applications to the next level by leveraging Machine Learning techniques to improve Relevance and implement automatic Recommendations and Query Intent capabilities in Fusion. This course explores how you can enrich your data through techniques such as Automatic Classification, Document Clustering, Anomaly Detection, and Natural Language Processing, and make it available to your applications. You will also learn how to implement and use techniques such as Query Intent Detection, Signals and Recommendations, Automatic Synonym Generation, and Automatic Mis-spelling Corrections in order to deliver the most personalized, contextual information and insights using the enriched data. This course also provides comprehensive hands-on lab exercises to help solidify the learning objectives.

Target Persona(s)

  • Data Architect
  • Data Scientist
  • Search Developer
  • Search Project Manager

Recommended Audience

Search Project Managers, Data Architects, Developers and Data-Scientists who are working on or considering a Fusion-based solution and are planning to implement Fusion’s machine learning capabilities will benefit from this course.

Pre-requisite

This training will introduce advanced Fusion Machine-Learning and AI topics and requires attendees to first take the Fusion Server Foundations 4.1 course. Basic experience with Linux OS and command-line tools is helpful but not required.

Skills and Concepts That You Will Learn

  • Introduction to AI/ML Jobs and the Types of Tasks and Properties Involved in Them
  • Understand how AI Jobs are Implemented in Fusion
  • Learn what AI Jobs Fusion Implements OOTB and what are Their Use-cases
  • Understand ML Grid Parameters and how to Use Them
  • Understand Signals and User Telemetry and Leveraging Them to Achieve Personalized Search Results
  • Hands-on Review of Signals and Learning their Impact on Relevance and Personalization
  • Understand Document Clustering ML Jobs, their Properties and Use-cases
  • Hand-on Configuring, Running and Tuning a Clustering Job in Fusion
  • Understand Classification ML Jobs, their Properties and Use-cases
  • Hand-on Configuring, Training and Running a Query Intent Classifier Job in Fusion
  • Review of the Fusion Experiments Framework
  • Hands-on Implementing an Experiments Job in Fusion
  • Understand Query Analytics and NLP in Fusion
  • Understand how to Implement Personalized Recommendations in Fusion
  • Hands-on Configuring and Running items-for-user and items-for-item Personalized Recommendations

Course Outline

  1. Introduction to AI
  2. Fusion Machine Learning Architecture
  3. Signals in Fusion
  4. Document Clustering
  5. Classification: Documents and Query Intent
  6. Experiments
  7. Query Analytics and Natural Language Processing
  8. Automated Recommendations
Paris