Raghuraman Balachandran of Amazon at Machine Learning Developers Summit 2019
summary
Covers building a data lake on AWS as the foundation for machine learning, discussing AWS services and architectural considerations for ingesting, storing, cataloging and securing data for ML workflows. Focuses on practical patterns and tooling from Amazon for setting up scalable, governed data lakes to support downstream analytics and ML.
AI-written summary · about
related talks
28mTurning Data into Knowledge
56mUnderstanding and achieving a modern data architecture
19mBuilding modern data lakes on Amazon S3
31mBest practices for building your data lake on Amazon S3
43mData Lake beyond the Buzzword
28mTurn Data Into Insights
43mManaging a Data Lake on AWS
42mModern Data Strategy on AWS
