We would love to hear your feedback about our show! Please take our survey here: [ Ссылка ]

AWS Supports You: Using Amazon SageMaker Canvas to Generate ML Predictions Without Writing Code gives viewers on the twitch.tv/aws channel an overview of Amazon SageMaker Canvas, the current state and issues with ML value creation, how to scale ML value creation by enabling analysts, and a thorough demo of how it works. This series showcases best practices and troubleshooting tips from AWS Support. This episode originally aired on April 11th, 2022.

Intro 0:00
Current State of ML Value Creation 5:36
How to Scale ML Value Creation 08:14
Challenges Analysts Face in Building ML 10:32
Intro to Amazon SageMaker Canvas 13:05
SageMaker Canvas Demo - Intro 21:47
Demo - Import and Join Data 26:06
Demo - Build Quick Model 31:32
Demo - Performance Metrics 35:59
Demo - Predictions 40:59
Demo - Standard Build 45:43
Demo - Studio Link Share 46:48
Demo - Other Problem Types 50:12
Demo - Unbalanced Dataset 50:46
Demo - Deploy Model 52:57
Demo - Explainability 53:33
Getting Started 54:42

Recommended Links:
Previous ASY episode on SageMaker - [ Ссылка ]

[ Ссылка ]

[ Ссылка ]

[ Ссылка ]

Amazon SageMaker Canvas Immersion Day
[ Ссылка ]

Subscribe:
More AWS videos - [ Ссылка ]
More AWS events videos - [ Ссылка ]

ABOUT AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers — including the fastest-growing startups, largest enterprises, and leading government agencies — are using AWS to lower costs, become more agile, and innovate faster.

#AWS #AmazonWebServices #CloudComputing

свернуть