Natural Language Search Training

Natural Language Search

Perhaps your team has done what it can with normal relevance methods? And now wants to move towards using Natural Language Processing (NLP) to improve understanding of your content and queries?

‘Natural Language Search’ is a 2 part training course to give your team the ability to use open source NLP tools to improve search relevance. This class helps you understand how to work with different NLP tools and libraries to recognize concepts and entities, understand customer query intent, differentiate models for your specific language use cases, avoid common pitfalls, and build a language-aware search platform.

If you’ve already attended our Think Like a Relevance Engineer course – contact us for a discount on Natural Language Search!

Who we are

OpenSource Connections believes in empowering search teams. OpenSource Connections has worked with open source search and applied Information Retrieval since 2007. We wrote the book Relevant Search and have pioneered open source relevance tuning tools like the Elasticsearch Learning to Rank plugin, Quepid and Splainer.

Your trainer

Your OpenSource Connections trainer is a relevance thought-leader actively working on real-life relevance issues. Natural Language Search Training is core to our mission of ‘empowering search teams’, so you get our best and brightest. We never send a trainer to just “read off slides”. We expect you to bring your hardest questions to our trainers. Our trainers expect to be challenged, and know how to handle unique twists on problems they’ve seen before.

What you’ll get out of it

You’ll learn about using language to improve search experience for your users. This includes practical how-to’s and hands-on labs for:

Leverage NLP tools to pre-process text and understand the basics
Recognize Dates, Quantities, Locations, and other Entities and use them in Search
Measure how accurately a model processes your text
Train NLP models to fit your language use cases
Classify query text for customer intent
Learn state of the art deep learning NLP transformer technology
Work Hands-on with NLP Libraries to build a language-aware search platform

Part One – Search, Language, and Tools

(delivered over 2 half days online or one day in person)

Goal for the day: Making Sense of Search with Language Enrichment. You’ll learn the core concepts of language structure and how NLP tools and models work, and how to use them for named entity recognition and query intent:

Introduction to NLP
Back to English Class! + LAB
Named Entities
Measurement + LAB
Values Search + LAB
Entity Location Search + LAB
Query Intent + LAB

Part Two – Natural Language Search

(delivered over 2 half days online or one day in person)

Goal for the day: Make a Neural Search Engine! We go deep into practical exercises of building a working natural language search engine, through the use of state of the art transformer NLP technology.

Vectors in Search + LAB
Introduction to Transformers and BERT + LAB
Fine-tuning Neural Search + LAB
Hosting Considerations & Model Performance
Putting it all together – the Natural Language Search Engine + LAB

Who should come to training?

This training is appropriate for members of the search team that have an interest in optimizing search with advanced programming techniques and natural language processing:

Search Engineers
Data Scientists
Data Engineers that use the search engine
Relevance engineers
Product team wanting exposure to natural language processing methods