Relevance and Scoring Mechanisms for RAGs
Master ranking algorithms and advanced scoring with Python. This course covers BM25, BERT, semantic similarity, and ensemble methods, focusing on effective document retrieval, evaluation, and optimization for sophisticated search systems.
What you'll learn
As data complexity increases, traditional search and ranking methods can become inadequate. In this course, Relevance and Scoring Mechanisms for RAGs, you'll explore cutting-edge ranking and scoring techniques to elevate your information retrieval systems.
First, you’ll learn about foundational ranking algorithms such as BM25 and cosine similarity to grasp the basics of document relevance.
Then, you’ll dive into sophisticated techniques like BERT embeddings and semantic matching with Sentence Transformers to handle complex queries and enhance retrieval accuracy.
Finally, you’ll gain practical skills in implementing and optimizing these techniques using Python libraries, including tuning and adapting methods for specific tasks and domains.
By the end of this course, you'll have a comprehensive understanding of modern ranking algorithms, be able to apply advanced scoring methods, and effectively optimize search and retrieval systems for improved performance and accuracy.
Table of contents
- Section 1 - Basic Ranking (Part 1) 5m
- Section 1 - Basic Ranking (Part 2) 4m
- Section 2 - Advanced Scoring Mechanisms 4m
- Section 3 - Implementation and Evaluation of Ranking Techniques (Part 1) 5m
- Section 3 - Implementation and Evaluation of Ranking Techniques (Part 2) 5m
- Section 4 - Optimization and Adaptation for Specific RAG Tasks (Part 1) 4m
- Section 4 - Optimization and Adaptation for Specific RAG Tasks (Part 2) 6m
About the author
Eduardo is a technology enthusiast, software architect and customer success advocate. He's designed enterprise .NET solutions that extract, validate and automate critical business processes such as Accounts Payable and Mailroom solutions for all types of organizations. He's designed and supported production systems for global names such as Coca Cola, Enel, Pirelli, Fiat-Chrysler, Xerox and many others. He's a well-known specialist in the Enterprise Content Management market segment, specifically... more