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Changelog Media์—์„œ ์ œ๊ณตํ•˜๋Š” ์ฝ˜ํ…์ธ ์ž…๋‹ˆ๋‹ค. ์—ํ”ผ์†Œ๋“œ, ๊ทธ๋ž˜ํ”ฝ, ํŒŸ์บ์ŠคํŠธ ์„ค๋ช…์„ ํฌํ•จํ•œ ๋ชจ๋“  ํŒŸ์บ์ŠคํŠธ ์ฝ˜ํ…์ธ ๋Š” Changelog Media ๋˜๋Š” ํ•ด๋‹น ํŒŸ์บ์ŠคํŠธ ํ”Œ๋žซํผ ํŒŒํŠธ๋„ˆ๊ฐ€ ์ง์ ‘ ์—…๋กœ๋“œํ•˜๊ณ  ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋ˆ„๊ตฐ๊ฐ€๊ฐ€ ๊ท€ํ•˜์˜ ํ—ˆ๋ฝ ์—†์ด ๊ท€ํ•˜์˜ ์ €์ž‘๋ฌผ์„ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐ๋˜๋Š” ๊ฒฝ์šฐ ์—ฌ๊ธฐ์— ์„ค๋ช…๋œ ์ ˆ์ฐจ๋ฅผ ๋”ฐ๋ฅด์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค https://ko.player.fm/legal.
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Generating "hunches" using smart home data ๐Ÿ  (Practical AI #132)

42:42
 
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Manage episode 291821534 series 1280399
Changelog Media์—์„œ ์ œ๊ณตํ•˜๋Š” ์ฝ˜ํ…์ธ ์ž…๋‹ˆ๋‹ค. ์—ํ”ผ์†Œ๋“œ, ๊ทธ๋ž˜ํ”ฝ, ํŒŸ์บ์ŠคํŠธ ์„ค๋ช…์„ ํฌํ•จํ•œ ๋ชจ๋“  ํŒŸ์บ์ŠคํŠธ ์ฝ˜ํ…์ธ ๋Š” Changelog Media ๋˜๋Š” ํ•ด๋‹น ํŒŸ์บ์ŠคํŠธ ํ”Œ๋žซํผ ํŒŒํŠธ๋„ˆ๊ฐ€ ์ง์ ‘ ์—…๋กœ๋“œํ•˜๊ณ  ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋ˆ„๊ตฐ๊ฐ€๊ฐ€ ๊ท€ํ•˜์˜ ํ—ˆ๋ฝ ์—†์ด ๊ท€ํ•˜์˜ ์ €์ž‘๋ฌผ์„ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐ๋˜๋Š” ๊ฒฝ์šฐ ์—ฌ๊ธฐ์— ์„ค๋ช…๋œ ์ ˆ์ฐจ๋ฅผ ๋”ฐ๋ฅด์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค https://ko.player.fm/legal.

Smart home data is complicated. There are all kinds of devices, and they are in many different combinations, geographies, configurations, etc. This complicated data situation is further exacerbated during a pandemic when time series data seems to be filled with anomalies. Evan Welbourne joins us to discuss how Amazon is synthesizing this disparate data into functionality for the next generation of smart homes. He discusses the challenges of working with smart home technology, and he describes how they developed their latest feature called โ€œhunches.โ€

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  • O'Reilly Media โ€“ Learn by doing โ€” Python, data, AI, machine learning, Kubernetes, Docker, and more. Just open your browser and dive in. Learn more and keep your teamsโ€™ skills sharp at oreilly.com/changelog
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1974 ์—ํ”ผ์†Œ๋“œ

Artwork
icon๊ณต์œ 
 
Manage episode 291821534 series 1280399
Changelog Media์—์„œ ์ œ๊ณตํ•˜๋Š” ์ฝ˜ํ…์ธ ์ž…๋‹ˆ๋‹ค. ์—ํ”ผ์†Œ๋“œ, ๊ทธ๋ž˜ํ”ฝ, ํŒŸ์บ์ŠคํŠธ ์„ค๋ช…์„ ํฌํ•จํ•œ ๋ชจ๋“  ํŒŸ์บ์ŠคํŠธ ์ฝ˜ํ…์ธ ๋Š” Changelog Media ๋˜๋Š” ํ•ด๋‹น ํŒŸ์บ์ŠคํŠธ ํ”Œ๋žซํผ ํŒŒํŠธ๋„ˆ๊ฐ€ ์ง์ ‘ ์—…๋กœ๋“œํ•˜๊ณ  ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๋ˆ„๊ตฐ๊ฐ€๊ฐ€ ๊ท€ํ•˜์˜ ํ—ˆ๋ฝ ์—†์ด ๊ท€ํ•˜์˜ ์ €์ž‘๋ฌผ์„ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐ๋˜๋Š” ๊ฒฝ์šฐ ์—ฌ๊ธฐ์— ์„ค๋ช…๋œ ์ ˆ์ฐจ๋ฅผ ๋”ฐ๋ฅด์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค https://ko.player.fm/legal.

Smart home data is complicated. There are all kinds of devices, and they are in many different combinations, geographies, configurations, etc. This complicated data situation is further exacerbated during a pandemic when time series data seems to be filled with anomalies. Evan Welbourne joins us to discuss how Amazon is synthesizing this disparate data into functionality for the next generation of smart homes. He discusses the challenges of working with smart home technology, and he describes how they developed their latest feature called โ€œhunches.โ€

Leave us a comment

Changelog++ members get a bonus 1 minute at the end of this episode and zero ads. Join today!

Sponsors:

  • O'Reilly Media โ€“ Learn by doing โ€” Python, data, AI, machine learning, Kubernetes, Docker, and more. Just open your browser and dive in. Learn more and keep your teamsโ€™ skills sharp at oreilly.com/changelog
  • Changelog++ โ€“ You love our content and you want to take it to the next level by showing your support. Weโ€™ll take you closer to the metal with no ads, extended episodes, outtakes, bonus content, a deep discount in our merch store (soon), and more to come. Letโ€™s do this!
  • Fastly โ€“ Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com.

Featuring:

Show Notes:

Something missing or broken? PRs welcome!

  continue reading

1974 ์—ํ”ผ์†Œ๋“œ

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