Free Download Azure Cognitive Search Indexing (With Cosmosdb & Functions)
Published 3/2023
Created by Ajay Gupta
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 41 Lectures ( 4h 18m ) | Size: 1.5 GB
Learn to build advanced Cognitive Search indexer pipelines using skillsets, caching, and run search queries with APIs
Free Download What you'll learn
Learn Azure Cognitive Search from scratch to advanced concepts
Use real-life data in cosmosdb as source, create search indexer and index to enable search
Learn Field Mapping, Synonym Map, Suggestions API, Filters, and Facets
Using incremental caching using highwatermark
Using Skills and Skillsets to enhance data
Search query using APIs: Simple, Fuzzy, Proximity, Wildcard, Regex, Geo-Spatial, and Term boosted searches.
Will set base by diving into Cosmosdb, storage account, and Azure function with HTTP and Cosmosdb Bindings
Requirements
Azure Account - free tier
Basic JavaScript
Description
Azure Cognitive Search (formerly known as "Azure Search") is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.Search is foundational to any app that surfaces text to users, where common scenarios include catalog or document search, online retail apps, or data exploration over proprietary content. When you create a search service, you'll work with the following capabilities:A search engine for full text search over a search index containing user-owned contentRich indexing, with lexical analysis and optional AI enrichment for content extraction and transformationRich query syntax for text search, fuzzy search, autocomplete, geo-search and moreProgrammability through REST APIs and client libraries in Azure SDKsAzure integration at the data layer, machine learning layer, and AI (Cognitive Services)We will also have a dive in Setting up Azure Account, CLI, Cosmosdb, Storage account and using storage explorer to create blobs. We are also going to enhance our search pipeline with Custom and In-build skills, We will define skillsets and map fields to indexer. For our use case we will use real life data. You will also learn to use different type of search queries via REST API you can run on index. This includes Simple, Fuzzy, geo-spatial, wildcard, regex, term boosting, and proximity searches.Will see some advaced features like using incremental caching, Synonym mapping, and suggestions or auto-complete apis.
Who this course is for
Developers
Architects
Technical Managers
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