AWS Bites

46. How do you do machine learning on AWS?


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The public cloud gives you amazing machine learning powers with a low barrier to entry. Once you know where to begin, you can quickly build solutions to process images, video, text and audio, as well as structured data. In this episode we talk about the managed AI services that are available on AWS and that require zero machine learning expertise (Rekognition, Polly, Transcribe, Forecast, Personalise, Comprehend, Lex, Textract, Translate). We will also talk about services you can use to create and run your own custom models (SageMaker). We will finally cover some different use cases and some of the things you need to consider before you do machine learning in production.

In this episode, we mentioned the following resources:

- AI as a Service book https://www.manning.com/books/ai-as-a-service

- Julien Simon’s YouTube channel: https://www.youtube.com/c/juliensimonfr

- Article by MIT researchers “Amazon’s Rekognition shows gender and ethnic bias”: https://venturebeat.com/2019/01/24/amazon-rekognition-bias-mit/

- Article “One year moratorium on police use of Rekognition”: https://www.aboutamazon.com/news/policy-news-views/we-are-implementing-a-one-year-moratorium-on-police-use-of-rekognition

This episode is also available on YouTube: https://www.youtube.com/AWSBites

You can listen to AWS Bites wherever you get your podcasts:

- Apple Podcasts: https://podcasts.apple.com/us/podcast/aws-bites/id1585489017

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- Google: https://podcasts.google.com/feed/aHR0cHM6Ly9hbmNob3IuZm0vcy82YTMzMTJhMC9wb2RjYXN0L3Jzcw==

- Breaker: https://www.breaker.audio/aws-bites

- RSS: ​​https://anchor.fm/s/6a3312a0/podcast/rss

Do you have any AWS questions you would like us to address?

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