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Over two days, gives you a solid foundation for applied Information Retrieval with Elasticsearch.

From the team behind Relevant Search; co-taught by Eric Pugh and Doug Turnbull. We teach you a practice for building smarter, more relevant search experiences with Elasticsearch. From measurement, to TF*IDF, to semantic search and learning to rank.

Agenda

Day One - Towards a ā€˜Relevance Centeredā€™ Enterprise

This day helps the class understand how working on relevance requires different thinking than other engineering problems. We teach you to measure search quality, take a hypothesis-driven approach to search projects, and safely ā€˜fail fastā€™ towards ever improving business KPIs

  • What is search?
  • Holding search accountable to the business
  • Search quality feedback
  • Hypothesis-driven relevance tuning
  • User studies for search quality
  • Using analytics & clicks to understand search quality

Day Two - Engineering Relevance with Elasticsearch

This day demonstrates relevance tuning techniques that actually work. Relevance canā€™t be achieved by just tweaking field weights: Boosting strategies, synonyms, and semantic search are discussed. The day is closed introducing machine learning for search (aka ā€œLearning to Rankā€).

  • Getting a feel for Elasticsearch
  • Signal Modeling (data modeling for relevance)
  • Dealing with multiple, competing objectives in search relevance
  • Synonym strategies that actually work
  • Taxonomy-based Semantic Search in Elasticsearch
  • Introduction to Learning to Rank

What Youā€™ll Get Out Of It

  • A practice for using Elasticsearch to improve relevance
  • Incorporating user and analytics feedback into relevance tuning
  • Measuring relevance, proving it has a business impact
  • Combining different ranking signals
  • Using taxonomies and synonyms to build semantic search
  • Bringing to bear machine learning resources on Learning to Rank

Your Trainers: Experienced Relevance Experts

Doug Turnbull and Eric Pugh are experienced search relevance experts. Doug is the author of Relevant Search, Eric Pugh is a founder of OpenSource Connections and regular speaker at conferences such as Haystack and Berlin Buzzwords. Doug and Eric have lead organizations on a number of projects using agile Test-Driven Relevance methodologies with Quepid, OpenSource Connections search relevance tool bench.

Style of Training: Small Group Workshop

Our trainers are not ā€˜stock tech trainerā€™ from central casting mindlessly reading slides. Our trainers expect to problem solve in real-time, and we want to hear your tough problems. As OpenSource Connectionā€™s mission is to ā€˜empower search teamsā€™, we see training as the central component to our mission. Our training is ā€˜workshop styleā€™ where much of the value is the interactions and knowledge sharing between the small class and the two trainers.

Who This Training is For

Some basic exposure to Elasticsearch is recommended, but not required. But even those with extensive Elasticsearch training will get value from this training as we teach Elasticsearch from the relevance perspective. Roles that would get value out of this training:

  • Search engineers
  • Data scientists
  • Data engineers
  • Machine learning engineers
  • Relevance engineers
  • Search product owners

Quotes From Past Attendees:

'Think Like a Relevance Engineer' has helped me think differently about how I solve Solr & Elasticsearch relevance problems"

Matt Corkum, Disruptive Technology Director,
Elsevier

What a positive experience! We have so many new ideas to implement after attending 'Think Like a Relevance Engineer' training.

Andrew Lee, Director of Engineering for Search
DHI

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