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ãƒ‰ãƒ©ãƒžã€Œã‚¤ã‚«ã‚²ãƒ¼ãƒ ã€ãŒé…ä¿¡å¾Œã‚ãšã‹17æ—¥ã§1å„„äººä»¥ä¸Šã®è¦–è´è€…æ•°ã‚’ç¨¼ããªã©ã€å‹•ç”»é…ä¿¡ã‚µãƒ¼ãƒ“ã‚¹ã®Netflixã¯ä¸–ç•Œä¸ã§åˆ©ç”¨ã•ã‚Œã€æ¥½ã—ã¾ã‚Œã¦ã„ã¾ã™ã€‚ãã‚“ãªNetflixã®ã‚µãƒ¼ãƒ“ã‚¹ã‚’æ”¯ãˆã‚‹ã‚·ã‚¹ãƒ†ãƒ ã®é¢ã«ã¤ã„ã¦ã€æµ·å¤–ãƒ¡ãƒ‡ã‚£ã‚¢ã®The VergeãŒã¾ã¨ã‚ã¦ã„ã¾ã™ã€‚ Why Netflix never goes down - The Verge https://www.theverge.com/22787426/netflix-cdn-open-connect å¤šãã®å‹•ç”»é…ä¿¡ã‚µãƒ¼ãƒ“ã‚¹ã«ã¨ã£ã¦ã€ã‚µãƒ¼ãƒãƒ¼ãƒ€ã‚¦ãƒ³ã‚„é€šä¿¡ã®é…å»¶ãªã©ãŒå¸¸ã«é ç—›ã®ç¨®ã¨ã—ã¦ä»˜ãã¾ã¨ã„ã¾ã™ã€‚Netflixã¯ã“ã‚Œã‚‰ã®å•é¡Œã‚’å›žé¿ã™ã‚‹ãŸã‚ã€ãŠã‚ˆã10å¹´ã«ã‚ãŸã‚Šç‹¬è‡ªã®CDNã€ŒOpen Connectã€ã‚’æ§‹ç¯‰ã—ã¦ãã¾ã—ãŸã€‚Open Connectã¯ãƒ†ãƒ¬ãƒ“ç•ªçµ„ã‚„æ˜ ç”»ã‚’é…ä¿¡ã™ã‚‹ãŸã‚ã«ç‰¹åˆ¥ã«æ§‹ç¯‰ã•ã‚ŒãŸNetflixã®ç¤¾å†…ã‚³ãƒ³ãƒ†ãƒ³ãƒ„é…ä¿¡ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã§ã€
braitom 2021/11/26
Netflix

cdn
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Netflix Android and iOS Studio Appsâ€Šâ€”â€Šnow powered by Kotlin Multiplatform
By David Henry & Mel Yahya Over the last few years Netflix has been developing a mobile app called Prodicle to innovate in the physical production of TV shows and movies. The world of physical production is fast-paced, and needs vary significantly between the country, region, and even from one production to the next. The nature of the work means weâ€™re developing write-heavy software, in a distribu
braitom 2020/11/02
Kotlin

Netflix
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Netflix CEO Explains Why He Pays Technologists Huge Salaries
For years, Netflix has maintained a reputation as a company that pays its techno logists huge salaries. Data has backed up that assertion; for example, crowdsourced compensation numbers fromÂ levels.fyiÂ suggest that Netflixâ€™s software engineersÂ can make nearly half a million dollars per year, well ahead of what they might earn at rivals such as Disney and Amazon. Why does the company pay so much? In
braitom 2020/09/30
å¤§äº‹ã€‚â€œThe reason the rock-star engineer is so much more valuable than his counterparts isnâ€™t unique to programming,â€ he wrote. â€œThe great software engineer is incredibly creative and can see conceptual patterns that others canâ€™t.â€

Netflix
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Netflixã‚’æ”¯ãˆã‚‹æŽ¨è–¦ã‚·ã‚¹ãƒ†ãƒ ã®è£å´ï½œmasa_kazama
ã‚¤ãƒ³ãƒˆãƒNetflixã¯ã€ã‚¹ãƒžãƒ›ã‚„PCãŒã‚ã‚Œã°ã€ã©ã“ã§ã‚‚ã„ã¤ã§ã‚‚ã€æ˜ ç”»ã‚„ãƒ‰ãƒ©ãƒžã‚’è¦‹æ”¾é¡Œã§æ¥½ã—ã‚€ã“ã¨ãŒã§ãã¾ã™ã€‚ä»Šå¹´ã¯ãŠå®¶æ™‚é–“ãŒå¢—ãˆãŸã“ã¨ã§ã€Netflixã‚’ã‚ˆã‚Šæº€å–«ã—ã¦ã„ã‚‹æ–¹ã‚‚å¤šã„ã®ã§ã¯ãªã„ã§ã—ã‚‡ã†ã‹ã€‚å®Ÿéš›ã«ã€2020å¹´1æœˆã€œ3æœˆã«ä¼šå“¡ãŒå…¨ä¸–ç•Œã§1600ä¸‡äººã»ã©å¢—ãˆã€åˆè¨ˆ1å„„8000ä¸‡äººã‚’è¶…ãˆã¦ã„ã¾ã™ã€‚ Netflixã‚’ã„ãã¤ã‹ã®æ•°å—ã§è¦‹ã¦ã¿ã‚‹ã¨ã€ã•ã‚‰ã«ãã®å‡„ã•ã«é©šã‹ã•ã‚Œã¾ã™ã€‚ ãƒ»å…¨ä¸–ç•Œã®ã‚¤ãƒ³ã‚¿ãƒ¼ãƒãƒƒãƒˆé€šä¿¡é‡(ä¸‹ã‚Š)ã®15%ã‚’NetflixãŒå ã‚ã¦ãŠã‚Šã€YouTubeã‚’è¶…ãˆã‚‹ä¸–ç•Œä¸€ã®å‹•ç”»ã‚µãƒ¼ãƒ“ã‚¹ ãƒ»æ™‚ä¾¡ç·é¡ãŒ20å…†å††è¶…ãˆ ãƒ»ã‚µãƒ–ã‚¹ã‚¯ãƒªãƒ—ã‚·ãƒ§ãƒ³åŽå…¥ãŒæœˆã€…ç´„1500å„„å†† ãã‚“ãªå¤šãã®ãƒ¦ãƒ¼ã‚¶ãƒ¼ã‚’æœ‰ã™ã‚‹Netflixã®é…åŠ›ã®ï¼‘ã¤ã«ã€æŽ¨è–¦ã‚·ã‚¹ãƒ†ãƒ ãŒã‚ã‚Šã¾ã™ã€‚Netflixã®ãƒ›ãƒ¼ãƒ ç”»é¢ã«ã¯ã€ä»Šè©±é¡Œã®ä½œå“ã‚„ãƒ¦ãƒ¼ã‚¶ãƒ¼ã«ãƒ‘ãƒ¼ã‚½ãƒŠãƒ©ã‚¤ã‚ºåŒ–ã•ã‚ŒãŸãŠã™ã™ã‚ã®ä½œå“ãŒä¸¦ã³ã¾ã™ã€‚ Googleã®æ¤œç´¢ã¨é•ã£ã¦ã€Netfl
braitom 2020/08/05
NetflixæŽ¨è–¦ã‚·ã‚¹ãƒ†ãƒ ã®æ´å²ã€ã©ã®ã‚ˆã†ã«æ”¹è‰¯ã•ã‚Œã¦ããŸã‹ã€æŽ¨è–¦ã‚·ã‚¹ãƒ†ãƒ ã®å…·ä½“ä¾‹ãªã©ãŒã¾ã¨ã‚ã‚‰ã‚Œã¦ã„ã‚‹ã€‚

Netflix
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Open-Sourcing riskquant, a library for quantifying risk
Netflix has a program in our Information Security department for quantifying the risk of deliberate (attacker-driven) and accidental losses. This program started on the Detection Engineering team with a home-grown Python library called riskquant, which weâ€™ve released as open source for you to use (and contribute to). Since that library was written, we have hired two amazing full-time Risk Engineer
braitom 2020/03/11
Netflixã®æƒ…å ±ã‚»ã‚ãƒ¥ãƒªãƒ†ã‚£ãƒãƒ¼ãƒ è£½ã®æ”»æ’ƒã‚„å¶ç™ºçš„ãªéŽå¤±ã®ãƒªã‚¹ã‚¯ã‚’å®šé‡åŒ–ã™ã‚‹ãƒ„ãƒ¼ãƒ«ã«ã¤ã„ã¦ã€‚æå¤±ã®é »åº¦ã‚„å¤§ãã•ã‚’å®šé‡åŒ–ã§ãã‚‹ã€‚Open Sourceã§å…¬é–‹ã•ã‚Œã¦ã„ã‚‹ã€‚ã»ãƒ¼é¢ç™½ã„ã€‚

security

Netflix
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Metaflow - a framework for real-life ML, AI, and data science
A framework for real-life ML, AI, and data science Open-source Metaflow makes it quick and easy to build and manage real-life ML, AI, and data science projects. Modeling Use any Python libraries for models and business logic. Metaflow helps manage library dependencies, locally and in the cloud. Deployment Deploy workflows to production with a single command and integrate with other systems through
braitom 2019/12/06
Netflixè£½ã®ãƒ‡ãƒ¼ã‚¿ã‚µã‚¤ã‚¨ãƒ³ã‚¹ç”¨Pythonãƒ©ã‚¤ãƒ–ãƒ©ãƒªã€‚

Netflix

python

data
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Python at Netflix
By Pythonistas at Netflix, coordinated by Amjith Ramanujam and edited by Ellen Livengood As many of us prepare to go to PyCon, we wanted to share a sampling of how Python is used at Netflix. We use Python through the full content lifecycle, from deciding which content to fund all the way to operating the CDN that serves the final video to 148 million members. We use and contribute to many open-sou
braitom 2019/05/01
Netflixã§ã®Pythonã®ä½¿ã‚ã‚Œæ–¹ã«ã¤ã„ã¦ã€‚CDNã®ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ãƒ‡ãƒã‚¤ã‚¹ã®é‹ç”¨ç®¡ç†éƒ¨åˆ†ã€ãƒ‘ãƒ¼ã‚½ãƒŠãƒ©ã‚¤ã‚¼ãƒ¼ã‚·ãƒ§ãƒ³ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã€æ©Ÿæ¢°å¦ç¿’ã‚¤ãƒ³ãƒ•ãƒ©ã€ç›£è¦–ã‚„è‡ªå‹•ä¿®å¾©ã®ãŸã‚ã®ãƒ„ãƒ¼ãƒ«ãªã©ã•ã¾ã–ã¾ãªã¨ã“ã‚ã§ä½¿ã£ã¦ã„ã‚‹ã€‚

python

Netflix
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Chaos Monkey Guide for Engineers - Tips, Tutorials, and Training
See how Gremlin helps organizations modernize their approach to reliability. PLATFORM OVERVIEW
braitom 2019/02/18
Chaos Monkeyã‚¬ã‚¤ãƒ‰ã€‚Chaos Monkeyã¨ã¯ä½•ã‹ã€é•·æ‰€ã¨çŸæ‰€ã€å®Ÿè·µæ–¹æ³•ãªã©ã®ãƒªã‚½ãƒ¼ã‚¹ãŒã¾ã¨ã‚ã‚‰ã‚Œã¦ã„ã‚‹ã€‚

Netflix

chaos-engineering
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Netflixã«ãŠã‘ã‚‹ãƒ•ãƒ«ã‚µã‚¤ã‚¯ãƒ«é–‹ç™ºè€…â€•é–‹ç™ºã—ãŸã‚‚ã®ãŒé‹ç”¨ã™ã‚‹ - CARTA TECH BLOG
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braitom 2019/02/06
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Netflix

engineering
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braitom 2019/01/07
Netflixã®å‹é”æ©Ÿèƒ½ã®å¤±æ•—ã¨ãã“ã‹ã‚‰å¾—ãŸæ•™è¨“ã«ã¤ã„ã¦ã€‚æ©Ÿèƒ½ã«é•·ãã“ã ã‚ã£ã¦ã—ã¾ã£ãŸç†ç”±ã€å¤±æ•—ã‹ã‚‰å¾—ã‚‰ã‚ŒãŸæ•™è¨“ãŒæ›¸ã‹ã‚Œã¦ã„ã‚‹ã€‚ã‚µãƒ³ã‚¯ã‚³ã‚¹ãƒˆã‚’ç„¡è¦–ã™ã‚‹ã€ãƒ—ãƒ©ã‚¤ãƒ‰ã‚„æƒ…ã‹ã‚‰é›¢ã‚ŒãŸåˆ¤æ–ã‚’è¡Œã†ãªã©ã€‚

management

Netflix
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A Netflix Web Performance Case Study â€“ Dev Channel â€“ Medium
tl;dr: There are no silver bullets to web performance. Simple static pages benefit from being server-rendered with minimal JavaScript. Libraries can provide great value for complex pages when used with care. Netflix is one of the most popular video streaming services. Since launching globally in 2016, the company has found that many new users are not only signing up on mobile devices but are also
braitom 2018/11/06
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Netflix

performance

Web
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braitom 2018/11/02
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Netflix
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braitom 2018/10/03
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Full Cycle Developers at Netflix
The year was 2012 and operating a critical service at Netflix was laborious. Deployments felt like walking through wet sand. Canarying was devolving into verifying endurance (â€œnothing broke after one week of canarying, letâ€™s push itâ€) rather than correct functionality. Researching issues felt like bouncing a rubber ball between teams, hard to catch the root cause and harder yet to stop from bounci
braitom 2018/05/26
Full cycle Developerã¨ã„ã†è€ƒãˆã€‚â€œ A full cycle developer thinks and acts like an SWE, SDET, and SRE. â€

netflix

engineer
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ã€ç¿»è¨³ã€‘ã€Œã‚·ãƒªã‚³ãƒ³ãƒãƒ¬ãƒ¼ã‹ã‚‰ç”Ÿã¾ã‚ŒãŸæœ€é«˜ã®æ–‡æ›¸ã€ã¨çµ¶è³›ã•ã‚ŒãŸNetflixã®ã‚«ãƒ«ãƒãƒ£ãƒ¼ã‚¬ã‚¤ãƒ‰å…¨æ–‡ - BppLOG
Netflixã®ä¼æ¥æ–‡åŒ–ã‚„ç¤¾å“¡ã®è¡Œå‹•è¦ç¯„ã‚’å®šã‚ãŸã‚«ãƒ«ãƒãƒ£ãƒ¼ã‚¬ã‚¤ãƒ‰ãŒå…¬é–‹ã•ã‚Œã¦ãŠã‚Šã€Facebookã®COOã®ã‚·ã‚§ãƒªãƒ«ãƒ»ã‚µãƒ³ãƒ‰ãƒãƒ¼ã‚°ãŒã€Œã‚·ãƒªã‚³ãƒ³ãƒãƒ¬ãƒ¼ã‹ã‚‰ç”Ÿã¾ã‚ŒãŸæœ€é«˜ã®æ–‡æ›¸ã€ã¨è©•ä¾¡ã—ã¦ã„ã¾ã™ã€‚ ãã®ã‚«ãƒ«ãƒãƒ£ãƒ¼ã‚¬ã‚¤ãƒ‰ã¯ã‚‚ã¨ã‚‚ã¨2009å¹´ã«ã‚¹ãƒ©ã‚¤ãƒ‰ã¨ã—ã¦å…¬é–‹ã•ã‚Œã€æœ€æ–°ç‰ˆã¯Netflixã®æŽ¡ç”¨ãƒšãƒ¼ã‚¸ä¸Šã«æŽ²è¼‰ã•ã‚Œã¦ã„ã¾ã™ã€‚ä»Šå›žã¯è¨±å¯ã‚’å¾—ã¦ç¿»è¨³ã™ã‚‹ã“ã¨ã«ã—ã¾ã—ãŸã€‚ Netflix Culture (åŽŸæ–‡) (ç›®æ¬¡) æœ¬ç‰©ã®ä¾¡å€¤è¦³ åˆ¤æ–åŠ› ã‚³ãƒŸãƒ¥ãƒ‹ã‚±ãƒ¼ã‚·ãƒ§ãƒ³ å¥½å¥‡å¿ƒ å‹‡æ°— æƒ…ç†± ç„¡ç§ç„¡æ¬² ã‚¤ãƒŽãƒ™ãƒ¼ã‚·ãƒ§ãƒ³ ä¸€ä½“æ€§ èª å®Ÿ å½±éŸ¿åŠ› ãƒ‰ãƒªãƒ¼ãƒ ãƒãƒ¼ãƒ è‡ªç”±ã¨è²¬ä»» æƒ…å ±ã«é€šã˜ãŸã‚ãƒ£ãƒ—ãƒ†ãƒ³ çµ±åˆ¶ã§ã¯ãªãå‰å¾Œé–¢ä¿‚ é«˜åº¦ã«æ•´åˆ—ã—ã€ç·©ãçµåˆã™ã‚‹ å“è¶Šæ€§ã‚’æŽ¢ã—æ±‚ã‚ã‚‹ ã¾ã¨ã‚ æœ€å¾Œã« ã‚¨ãƒ³ã‚¿ãƒ¼ãƒ†ã‚¤ãƒ³ãƒ¡ãƒ³ãƒˆã¯ã€å‹æƒ…ã®ã‚ˆã†ã«ã€äººé–“ãŒåŸºæœ¬çš„ã«å¿…è¦ã¨ã—ã¦ã„ã‚‹ã‚‚ã®ã§ã™ã€‚ã‚¨ãƒ³ã‚¿ãƒ¼ãƒ†ã‚¤ãƒ³ãƒ¡ãƒ³ãƒˆã¯ç§ãŸã¡ã®æ„Ÿã˜æ–¹ã‚’å¤‰ãˆã€ç§ãŸã¡ã«å…±é€šç‚¹ã‚’ã‚‚ãŸã‚‰ã—
braitom 2018/05/20
Netflix

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management
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Netflixã«ãŠã‘ã‚‹æ—¥æœ¬èªžå—å¹•ã®å°Žå…¥
(Please note that this article is a localized (to Japanese) version of a corresponding tech blog article in the English language) Netflixã§ã¯ã€2015å¹´9æœˆã®æ—¥æœ¬ã«ãŠã‘ã‚‹é…ä¿¡ã‚µãƒ¼ãƒ“ã‚¹é–‹å§‹æ™‚ã‹ã‚‰æ—¥æœ¬èªžå—å¹•ã‚’æä¾›ã—ã¦ã„ã¾ã™ã€‚ ä»Šå›žã®ãƒ–ãƒã‚°ã§ã¯ã€æ—¥æœ¬èªžå—å¹•æä¾›ã«è‡³ã‚‹ã¾ã§ã®æŠ€è¡“çš„ãªå–ã‚Šçµ„ã¿ã«ã¤ã„ã¦èª¬æ˜Žã—ã¾ã™ã€‚ å—å¹•ã‚½ãƒ¼ã‚¹ãƒ•ã‚¡ã‚¤ãƒ«ã®ä»•æ§˜ã€å—å¹•ã‚½ãƒ¼ã‚¹ãƒ•ã‚¡ã‚¤ãƒ«ã‹ã‚‰Netflixé…ä¿¡ç”¨å—å¹•ã¸ã®å¤‰æ›ãƒ¢ãƒ‡ãƒ«ã€Netflixã«ãŠã‘ã‚‹æ—¥æœ¬èªžå—å¹•ã®ç´å“ãƒ¢ãƒ‡ãƒ«ãªã©ã‚’å–ã‚Šä¸Šã’ã¾ã™ã€‚ã•ã‚‰ã«ã€W3Cå—å¹•è¦æ ¼Timed Text Markup Language 2 (TTML2)å°Žå…¥ã«å‘ã‘ãŸå¯¾å¿œã«ã¤ã„ã¦ã‚‚è§¦ã‚Œã¾ã™ã€‚ 2014å¹´ã®çµ‚ç›¤ã«ã‹ã‘ã¦ã€Netflixã§ã¯2015å¹´9æœˆã«äºˆå®šã—ã¦ã„ãŸæ—¥
braitom 2018/05/14
netflix
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Titus, the Netflix container management platform, is now open source
by Amit Joshi, Andrew Leung, Corin Dwyer, Fabio Kung, Sargun Dhillon, Tomasz Bak, Andrew Spyker, Tim Bozarth Today, we are open-sourcing Titus, our container management platform. Titus powers critical aspects of the Netflix business, from video streaming, recommendations and machine learning, big data, content encoding, studio techno logy, internal engineering tools, and other Netflix workloads. Ti
braitom 2018/04/22
Netflixã®ã‚³ãƒ³ãƒ†ãƒŠç®¡ç†ãƒ—ãƒ©ãƒƒãƒˆãƒ•ã‚©ãƒ¼ãƒ ãŒOSSåŒ–ã•ã‚ŒãŸã¨ã®ã“ã¨ã€‚Apache Mesosä¸Šã§å‹•ãã‚ˆã†ä½œã‚‰ã‚Œã¦ã„ã‚‹ã€‚AWSã®å„æ©Ÿèƒ½ã¨ã‚·ãƒ¼ãƒ ãƒ¬ã‚¹ã«çµ±åˆã•ã‚Œã¦ã„ã‚‹ã€‚

docker

netflix
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PRINCIPLES OF CHAOS ENGINEERING - Principles of chaos engineering
PRINCIPLES OF CHAOS ENGINEERING Last Update: 2019 March (changes) Chaos Engineering is the discipline of experimenting on a system in order to build confidence in the systemâ€™s capability to withstand turbulent conditions in production. Advances in large-scale, distributed software systems are changing the game for software engineering. As an industry, we are quick to adopt practices that increase
braitom 2018/01/29
â€œChaos Engineering is a powerful practice that is already changing how software is designed and engineered at some of the largest-scale operations in the world. â€

engineering

netflix
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Implementing Japanese Subtitles on Netflix
Japanese subtitles were first made available on the Netflix service as a part of the Japanese launch in September 2015. This blog post provides a technical description of the work we did leading up to this launch. We cover topics including our specification for source subtitle files, the transf ormation model from source subtitle files to those deliverable on the Netflix service, the model for deli
braitom 2017/12/12
Netflix

japanese
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Artwork Personalization at Netflix
By Ashok Chandrashekar, Fernando Amat, Justin Basilico and Tony Jebara For many years, the main goal of the Netflix personalized recommendation system has been to get the right titles in front each of our members at the right time. With a catalog spanning thousands of titles and a diverse member base spanning over a hundred million accounts, recommending the titles that are just right for each mem
braitom 2017/12/10
Netflixã®ã‚¢ãƒ¼ãƒˆãƒ¯ãƒ¼ã‚¯ã®ãƒ‘ãƒ¼ã‚½ãƒŠãƒ©ã‚¤ã‚¼ãƒ¼ã‚·ãƒ§ãƒ³æ–¹æ³•ã«ã¤ã„ã¦

Netflix

machineLearning

personalization
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