AI & ML Search with OpenSearch (elasticsearch + AI/ML)
About this course
Elasticsearch is a well-known search platform adopted in enterprises, SMBs and startups. Elasticsearch excels at lexical search use cases using BM25 algorithm , that is built on top of Lucene. However, with the advent of AI and large language models, Semantic Search, Hybrid Search, Neural Search, Multi-modal search etc. have become more of a norm than rarity. OpenSearch (originally a fork of Elasticsearch started in 2021) has gained immense popularity and adoption in open source, and enterprise communities with its Apache open source license and a Linux foundation project. While providing parity with all the lexical search capabilities of elasticsearch, OpenSearch integrates with LLM models (e.g. sentence transformers) , providers like OpenAI, Cohere, Anthropic and defines agentic workflows. As a win, Oracle switched to OpenSearch for its PeopleSoft search capabilities. AWS provides Opensearch-as-a-service on its cloud and that already speaks to the production readiness.AI & ML Search with OpenSearch course provides end-end training on installing, configuring and understanding OpenSearch , while implementing real search use cases like retrieval-augmented-generation (RAG), agentic workflows and migrating from Elasticsearch to OpenSearch. Emphasis has been laid on AI/ML use cases more than the traditional/lexical concepts, though the latter is covered for historical context. To compare Elasticsearch (ELK stack) & OpenSearch, we can roughly equate the below:Elasticsearch ~ OpenSearchLogstash ~ Data PrepperKibana ~ OpenSearch Dashboards OpenSearch is a fast moving platform in terms of its releases and features. We will be using version 2.17 which is production-ready as of September 2024. Docker has been extensively used in the course to ensure execution reproducibility of the entire course code. I am excited to be your instructor and hoping you resonate the same excitement !
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What you'll learn
- Installing and configuring OpenSearch
- Implementing search use cases like retrieval-augmented generation
- Understanding the differences between Elasticsearch and OpenSearch
- Integrating OpenSearch with large language models
Course objectives
- To provide hands-on training in using OpenSearch
- To highlight the advantages of AI/ML in search technologies
- To prepare participants for transitioning from Elasticsearch to OpenSearch
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