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Artificial Intelligence in Search Training
In this training, you will learn how to design and implement intelligent natural language search leveraging Open Source software.
You will learn about language modelling, vector-based search and how to integrate it with Apache Lucene/Solr and Elasticsearch.
Public Training sessions
First session
Natural Language Processing
This session explores various tasks in NLP that are useful to improve the quality of your search system and how to integrate them into your search engine, using open source software.
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- Public session no more available
Second session
Vector-Based Search and Augmenting the Inverted Index
This session explores approaches in sparse and dense vector retrieval, and you are going to learn how to integrate the power of deep learning techniques with your inverted index.
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- Public session no more available
Third session
BERT and Transformers
This session gives you a better understanding of how BERT works and how you can integrate it with your search architecture to improve your relevance.
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- Public session no more available
Fourth session
Open Source Approaches
This session explores the state of the art of how this innovative approach is supported by Open Source search engines such as Elasticsearch, Apache Solr, OpenSearch and Vespa.
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- Recorded version available
Choose the number of sessions to buy
2 SESSIONS
£ 650,00 By Purchasing the training You Accept our Training’s Terms and Conditions
Buy the first two sessions of this training
• Natural Language Processing
• Vector-Based Search and Augmenting the Inverted Index
3 SESSIONS
£ 850,00 By Purchasing the training You Accept our Training’s Terms and Conditions
Buy the first three sessions of this training
• Natural Language Processing
• Vector-Based Search and Augmenting the Inverted Index
• BERT and Transformers
4 SESSIONS
£ 1000,00 By Purchasing the training You Accept our Training’s Terms and Conditions
Buy all the sessions of this training
• Natural Language Processing
• Vector-Based Search and Augmenting the Inverted Index
• BERT and Transformers
• Open Source Approaches
Private and recorded training
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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 training is your perfect choice!
You can choose between online or live training.
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- In-presence or Online
- Tailored training
- Top expert trainers
- Certificate of Attendance
Based on experience with leading companies including
feedback from past students
"The course has certainly generated many interesting ideas, but first we have to fill some gaps.
The positive feedback I had about your professionalism and skills in the areas of information retrieval and AI makes me think that you can definitely be an important partner for the growth and development of our products."
The positive feedback I had about your professionalism and skills in the areas of information retrieval and AI makes me think that you can definitely be an important partner for the growth and development of our products."
Dario Rigolin
Founder
PREREQUISITES
• Basic understanding of Search Engines and Machine Learning.
WHAT YOU WILL LEARN
• How to integrate natural language processing techniques with your search engine
• How to use pre-trained language models and fine-tune them for your specific use case
• The pros/cons of vector-based search
• How to do that with Apache Lucene/Solr and Elasticsearch
INTENDED AUDIENCE
• Software Engineers
• Data Scientists
• Machine Learning passionates.
// Artificial Intelligence in Search Training
Our Trainers
Alessandro Benedetti
APACHE LUCENE/SOLR COMMITTER
APACHE SOLR PMC MEMBER
Alessandro Benedetti is the founder of Sease Ltd.
Alessandro has been involved from the beginning to the Apache Solr Learning To Rank plugin developments carried over by Bloomberg.
Over the years he has worked in various Learning To Rank projects and solutions including the contribution to Apache Solr of the Interleaving capability.
Anna Ruggero
R&D Search Software Engineer, her focus is on the integration of Information Retrieval systems with advanced Machine Learning, Neural Search models ad Recommender Systems.
She likes to find new solutions that integrate her work as a Search Consultant with the latest academic studies.
Ilaria Petreti
Data Scientist, passionate about the world of Artificial Intelligence. She loves applying Data Mining and Machine Learning techniques to help companies making careful data-driven decisions and increase their efficiency.
Full Program
Natural Language Processing
Introduction
NLP tasks useful for Search
Open Source Libraries Overview
Text and Speech Processing(Optical Character Recognition, Speech Recognition, Text to Speech, Tokenization)
Morphological Analysis(Stemming/Lemmatization, Part Of Speech Tagging)
Syntactic Analysis(Sentence Breaking)
Lexical Semantics(Named Entity Recognition and Linking, Sentiment Analysis, Word Sense Disambiguation)
Discourse(Coreference Resolution)
Implicit Semantic(Topic Segmentation and Recognition)
Higher Level Application(Automatic Summarization, Grammatical Error Correction, Machine Translation, Natural Language Understanding)
- Hands on Exercises
Deep Learning for Search
- A bit of history (challenges with exact matching, Deep Learning, semantic search)
- Word Embeddings
- Hands on Exercises: let’s start generating and using word embeddings
- BERT and transformers
- Hands on Exercises: let’s use BERT
- Model fine-tuning (pairwise learning, Margin-MSE aka DistilBERT)
- Hands on Exercises: Fine-tuning with pairwise learning
- Similarity search of dense vectors
- Hands on Exercises: Perform ANN search
- Augmenting the inverted index (document expansion and emphasize important terms)
- Hands on Exercises: performing document expansion
Vector Based Search
- How Open Source Search Engines cover the functionality (Apache Lucene/Solr, Elasticsearch and Vespa)
- Hands on Exercises: let’s run Vector-based search in Open Source search engines
Query Level
- Query Intent Classification
- Hands on Exercises: recognise the user intent with Open Source
- Zero result queries
- Hands on Exercises: improvement for zero result queries with Open Source backed techniques
Evaluation & Explainability
- Measure your progress
- Explainable artificial intelligence