// Learning To Rank training
OpenSearch Integration
With the Learning To Rank (or LTR for short) plugin, you can configure and run machine-learned ranking models in OpenSearch. The module also supports feature extraction inside OpenSearch. The only thing you need to do outside OpenSearch is to train your own ranking model.
This training illustrates how you can use the OpenSearch LTR component to integrate machine learning with your search pipeline.
Recorded
coming soon
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
12th 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
coming soon
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 OpenSearch Search Engine
- How to deploy your features and your models
- How to execute re-ranking queries with your updated model
- How to extract features with OpenSearch
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. OpenSearch integration
Learn the intricacies of seamlessly integrating ranking models with OpenSearch. Understand the integration process, from indexing data to querying, and explore optimization techniques for efficient OpenSearch integration. Gain practical insights into leveraging OpenSearch to enhance search relevance using ranking models.
2. Features Management
Navigate through the essentials of managing features for ranking models. Explore the process of selecting, engineering, and transforming features to optimize model performance. Understand how feature management contributes to the overall effectiveness of your ranking models and influences search relevance.
3. Ranking Models Management
Explore the management aspects of ranking models throughout their lifecycle. Learn best practices for model versioning, deployment, and monitoring. Understand how to adapt and optimize ranking models based on evolving business requirements and user feedback, ensuring continuous improvement and relevance.
4. How to Rerank Search Results
Understand the concept of result reranking and its significance in refining search outcomes. Explore strategies and techniques for reranking search results based on dynamic factors such as user behavior, context, and business priorities. Gain hands-on experience in implementing result reranking to elevate search relevance.
5. 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.
6. 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 OpenSearch Integration training 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!