// Learning To Rank training
How to Build your Training Set and Train your Model

With LTR becoming more and more popular, organizations struggle with the problem of how to collect and structure relevance signals necessary to train their ranking models.

This training is a technical guide to explore and master various techniques to generate your training set(s) correctly and efficiently. 

PREREQUISITES

• Basic understanding of Search Engines and Machine Learning

WHAT YOU WILL LEARN

• Model and collect the necessary feedback from the users (implicit or explicit)
• Calculate for each training sample a relevance label that is meaningful and not ambiguous (Click Through Rate, Sales Rate …)
• Transform the raw data collected in an effective training set (in the numerical vector format most of the LTR training libraries expect)
• Use open source libraries to train your model

INTENDED AUDIENCE

• Technical Managers
• Data scientists
• Software Engineers
• Developers
• Machine Learning passionates

Based on experience with leading companies including

Watch the intro video

Public Training

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  • Live on Zoom
  • Top expert trainers
  • Certificate of Attendance
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Pre-recorded

coming soon

We are working to provide a pre-recorded version of our bestseller training. If you want to receive an email as soon as we publish it, subscribe to our newsletter.
  • Top expert trainers
  • Q&A by e-mail
  • Certificate of Attendance
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Private

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If you are looking for intensive sessions tailored on your (or your team) experience, then private trainings are your perfect choice! You can choose between online or live trainings.
  • In-presence or Online
  • Tailored training
  • Top expert trainers
  • Certificate of Attendance
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// Learning To Rank How to build your training set and train your model

Our Trainers

Alessandro Benedetti

APACHE LUCENE/SOLR COMMITTER
APACHE SOLR PMC MEMBER

Alessandro has been involved in designing and developing search-relevant solutions from 2010.
Over the years he has worked on various projects, with various open source technologies aiming to build search solutions able to satisfy the user information needs, often integrating such solutions with machine learning and artificial intelligence technologies.

Andrea Gazzarini

RRE CREATOR

RRE Creator Andrea Gazzarini is a curious software engineer, mainly focused on the Java language and Search technologies. With more than 15 years of experience in various software engineering areas, his adventure in the search world began in 2010, when he met Apache Solr and later Elasticsearch.    

Full Program

  • Libraries Overview
    • Ranklib
    • XGBoost
  • Hands On Exercises: Let’s train a model using XGBoost
Frequently Asked Question

The Learning To Rank How to build your training set and train your model trainings will take place live on zoom!
We are working on being able to provide a recording of the training for those interested.

Everyone can participate on this training, the only prerequisites are written just over there!

Learning To Rank How to build your training set and train your model training last 4 hours.

You will be able to ask every question you have during the training!

Your teachers will be:
  – Alessandro Benedetti, Apache Lucene/Solr committer and Apache Solr PMC member.
  – Andrea Gazzarini, RRE Creator with more than 15 years of experience in various software engineering areas.

Sure, at the end of the training you will receive a certificate of attendance by e-mail.

If you can’t attend last minute you can contact us and reschedule on a different date with our team. Bear in mind this will have to be a private training.  

Yes, you can contact our Sales responsible Oriol Serra and find the best option for you and your team!

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