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Meeting Summary

ADT302 - Democratize Data Preparation for Analytics & Machine Learning: A Hands-On Lab

Session Description

Machine learning (ML) outcomes are only as good as the data they are built upon. Preparing data for ML is time consuming and cumbersome; “data wrangling” for analytics can consume over 80% of project effort. ML Wrangling Assistant, based on Trifacta running on AWS, streamlines ML applications so teams can focus on the work that matters—creating accurate predictions that improve products, services, and organizational efficiency. In this lab, we cover one of two data preparation use cases. Marketing Analytics analyzes web ads by cleaning and transforming ecommerce transactions in a relational table combined to a clickstream semi-structured log file. Cross-Sell Analytics explores, structures, standardizes, and combines multiple file types (CSV, JSON, Excel) to create a single, consistent view of customers. Final outputs are the categorical features and attributes to train, test, and validate the data sets required by Amazon SageMaker to perform ML modeling.

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Additional Information
Builders Session
AdTech
300 - Advanced
Please note that session information is subject to change.
Aria
Session Schedule