Beginners Guide To AWS Glue ML Transformations

In this video we take a look at AWS Glue and it's machine learning capabilities. I guide you through an AWS tutorial where we build an ML model through AWS Glue which matchings records together. 00:00 - Intro 00:16 - What We WIll Cover 01:19 - Hands On Tutorial Git Hub https://github.com/johnny-chivers/glueML Website https://johnnychivers.co.uk AWS https://docs.aws.amazon.com/glue/late... This tutorial guides you through the actions to create and manage a machine learning (ML) transform using AWS Glue. Before using this tutorial, you should be familiar with using the AWS Glue console to add crawlers and jobs and edit scripts. You should also be familiar with finding and downloading files on the Amazon Simple Storage Service (Amazon S3) console. In this example, you create a FindMatches transform to find matching records, teach it how to identify matching and nonmatching records, and use it in an AWS Glue job. The AWS Glue job writes a new Amazon S3 file with an additional column named match_id. The source data used by this tutorial is a file named dblp_acm_records.csv. This file is a modified version of academic publications (DBLP and ACM) available from the original DBLP ACM dataset. The dblp_acm_records.csv file is a comma-separated values (CSV) file in UTF-8 format with no byte-order mark (BOM). A second file, dblp_acm_labels.csv, is an example labeling file that contains both matching and nonmatching records used to teach the transform as part of the tutorial.