Description:Entity resolution is a key analytic technique that enables you to identify multiple data records that refer to the same real-world entity. With this hands-on guide, product managers, data analysts, and data scientists will learn how to add value to data by cleansing, analyzing, and resolving datasets using open source Python libraries and cloud APIs.Author Michael Shearer shows you how to scale up your data matching processes and improve the accuracy of your reconciliations. You'll be able to remove duplicate entries within a single source and join disparate data sources together when common keys aren't available. Using real-world data examples, this book helps you gain practical understanding to accelerate the delivery of real business value.With entity resolution, you'll build rich and comprehensive data assets that reveal relationships for marketing and risk management purposes, key to harnessing the full potential of ML and AI. This book Challenges in deduplicating and joining datasetsExtracting, cleansing, and preparing datasets for matchingText matching algorithms to identify equivalent entitiesTechniques for deduplicating and joining datasets at scaleMatching datasets containing persons and organizationsEvaluating data matchesOptimizing and tuning data matching algorithmsEntity resolution using cloud APIsMatching using privacy-enhancing technologiesWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Hands-On Entity Resolution: A Practical Guide to Data Matching with Python. To get started finding Hands-On Entity Resolution: A Practical Guide to Data Matching with Python, you are right to find our website which has a comprehensive collection of manuals listed. Our library is the biggest of these that have literally hundreds of thousands of different products represented.
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PDF, EPUB & Kindle Edition
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ISBN
1098148444
Hands-On Entity Resolution: A Practical Guide to Data Matching with Python
Description: Entity resolution is a key analytic technique that enables you to identify multiple data records that refer to the same real-world entity. With this hands-on guide, product managers, data analysts, and data scientists will learn how to add value to data by cleansing, analyzing, and resolving datasets using open source Python libraries and cloud APIs.Author Michael Shearer shows you how to scale up your data matching processes and improve the accuracy of your reconciliations. You'll be able to remove duplicate entries within a single source and join disparate data sources together when common keys aren't available. Using real-world data examples, this book helps you gain practical understanding to accelerate the delivery of real business value.With entity resolution, you'll build rich and comprehensive data assets that reveal relationships for marketing and risk management purposes, key to harnessing the full potential of ML and AI. This book Challenges in deduplicating and joining datasetsExtracting, cleansing, and preparing datasets for matchingText matching algorithms to identify equivalent entitiesTechniques for deduplicating and joining datasets at scaleMatching datasets containing persons and organizationsEvaluating data matchesOptimizing and tuning data matching algorithmsEntity resolution using cloud APIsMatching using privacy-enhancing technologiesWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Hands-On Entity Resolution: A Practical Guide to Data Matching with Python. To get started finding Hands-On Entity Resolution: A Practical Guide to Data Matching with Python, you are right to find our website which has a comprehensive collection of manuals listed. Our library is the biggest of these that have literally hundreds of thousands of different products represented.