// Learning To Rank training
Apache Solr Integration
With the Learning To Rank (or LTR for short) module, you can configure and run machine-learned ranking models in Solr. The module also supports feature extraction and interleaving inside Solr.
The only thing you need to do outside Solr is train your own ranking model.
This training illustrates how you can use the Apache Solr LTR component to integrate machine learning with your search pipeline.
Recorded
£ 150,00
If you are not able to attend public training, this is the best option for you. You will be able to take the course at your own pace and rhythm and learn whenever it fits your schedule and mood.
- Top expert trainers
- Q&A by e-mail
- Certificate of Attendance
Public classroom
£ 250,00
SCHEDULE
14th March 2024
3:00 – 7:00 PM GMT
- Live on Zoom
- Top expert trainers
- Certificate of Attendance
Private
ask for quote
If you are looking for intensive sessions tailored to your (or your team’s) experience, then private training is your perfect choice!
- In presence or Online
- Tailored Training
- Top Expert Trainers
- Certificate of Attendance
Recorded
£ 150,00
If you are not able to attend public training, this is the best option for you. You will be able to take the course at your own pace and rhythm and learn whenever it fits your schedule and mood.
- Top expert trainers
- Q&A by e-mail
- Certificate of Attendance
Private
ask for quote
If you are looking for intensive sessions tailored to your (or your team’s) experience, then private training is your perfect choice!
- In presence or Online
- Tailored Training
- Top Expert Trainers
- Certificate of Attendance
Based on experience with leading companies including
Based on experience with leading companies including
PREREQUISITES
• Basic understanding of Search Engines and Machine Learning
• Basic understanding of how Learning to Rank works
WHAT YOU WILL LEARN
- How to integrate Machine Learning with your Solr Search Engine
- How to deploy your features and your models
- How to execute re-ranking queries with your updated model
- How to do interleaving with Solr
- How to log features with Solr
INTENDED AUDIENCE
• Technical Managers
• Data scientists
• Software Engineers
• Developers
• Machine Learning passionates
Your 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.
Anna Ruggero
R&D Search Software Engineer, her focus is on the integration of Information Retrieval systems with advanced Machine Learning, Natural Language Processing and Data Mining algorithms. She likes to find new solutions that integrate her work as a Search Consultant with the latest Academia studies.
The schedule
The training session is meticulously structured for optimal comprehension and retention.
It commences with a comprehensive 1-hour theory session, followed by a brief 15-minute test to assess understanding. Subsequently, participants engage in a 45-minute Q&A segment, fostering interactive learning and clarification of concepts. The training then resumes with another 1-hour theory module, another 15-minute evaluation test, and concludes with a final 45-minute Q&A session to consolidate knowledge and address any remaining queries.
3:00-4:00 theory session
4:00-4:15 test
4:15-5:00 Q&A segment
5:00-6:00 theory session
6:00-6:15 test
6:15-7:00 Q&A segment
Topics
1. Apache Solr integration
In the Learning to Rank integration with Apache Solr section, we focus on the minimal requirements essential for seamless functionality. Explore the key elements to incorporate within Solr, ensuring a smooth and effective implementation of the LTR module.
2. Features Management
In the section on defining features for an LTR model in Solr, explore the varied feature types supported and associated APIs. Learn how to effectively structure and leverage features to optimize your Learning to Rank model within the Solr framework.
3. Ranking Models Management
Dive into Solr’s support for diverse LTR model types. Learn how to define and implement LTR models within Solr, exploring associated APIs. Uncover the flexibility and capabilities Solr offers in tailoring Learning to Rank models to your specific needs.
4. How to Rerank Search Results
In this hands-on section, discover the practical steps for reranking in Solr. Through concrete examples, witness the transformative impact on search results. Learn how to incorporate external information at query time and implement interleaving techniques for enhanced ranking strategies.
5. INTERLEAVING
Interleaving in Apache Solr Learning to Rank has been contributed to the Open Source community by Sease (read our blogpost about the Apache Solr – Learning to Rank Interleaving). In the “how to rerank search results” part of the training, we will see this online evaluation approach for information retrieval systems that compares ranking functions by mixing their results and interpreting the users’ implicit feedback.
6. Extract Features from the Results
In this section, learn to extract LTR-related features from documents at query time. Explore relevant parameters and APIs for feature extraction. Uncover the practical benefits of extracting features dynamically exploring their different ways of use in Learning to Rank scenarios.
7. Live Exercises
Embark on interactive exercises crafted to reinforce training concepts. While we guide you through each exercise, the hands-on practice will be facilitated post-training. A shared repository ensures you can delve into practical scenarios, work with code examples, and apply ranking models confidently at your own pace.
FAQ
The Learning To Rank Apache Solr Integration 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 Apache Solr Integration 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.
– Anna Ruggero, R&D Software Engineer at Sease.
Sure, at the end of the training you will receive a certificate of attendance by e-mail.
If you need it, you can consult our Training’s Terms and Conditions.
Yes, you can contact us and find the best option for you and your team!