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	<title>ab-testing &#8211; Noise</title>
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		<title>Sequential Testing Keeps the World Streaming Netflix Part 2: Counting Processes</title>
		<link>https://noise.getoto.net/2024/03/18/sequential-testing-keeps-the-world-streaming-netflix-part-2-counting-processes/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Mon, 18 Mar 2024 12:46:46 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[devops]]></category>
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					<description><![CDATA[Michael Lindon, Chris Sanden, Vache Shirikian, Yanjun Liu, Minal Mishra, Martin TingleyHave you ever encountered a bug while streaming Netflix? Did your title stop unexpectedly, or not start at all? In the first installment of this blog series on seque...]]></description>
		
		
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		<title>Netflix Original Research: MIT CODE 2023</title>
		<link>https://noise.getoto.net/2023/11/27/netflix-original-research-mit-code-2023/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Mon, 27 Nov 2023 20:59:14 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
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					<description><![CDATA[Netflix was thrilled to be the premier sponsor for the 2nd year in a row at the 2023 Conference on Digital Experimentation (CODE@MIT) in Cambridge, MA. The conference features a balanced blend of academic and industry research from some wicked smart fo...]]></description>
		
		
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		<title>Netflix: A Culture of Learning</title>
		<link>https://noise.getoto.net/2022/01/25/netflix-a-culture-of-learning/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Tue, 25 Jan 2022 16:23:45 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[decision-making]]></category>
		<category><![CDATA[experimentation]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Colin McFarland, Mihir Tendulkar, and Travis BrooksThis is the last post in an overview series on experimentation at Netflix. Need to catch up? Earlier posts covered the basics of A/B te...]]></description>
		
		
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		<title>Experimentation is a major focus of Data Science across Netflix</title>
		<link>https://noise.getoto.net/2022/01/11/experimentation-is-a-major-focus-of-data-science-across-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Tue, 11 Jan 2022 16:09:13 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[decision-making]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Colin McFarland, Andy Rhines, Sophia Liu, Mihir Tendulkar, Kevin Mercurio, Veronica Hannan, Ting-Po LeeEarlier posts in this series covered the basics of A/B tests (Part 1 and Part 2 ), ...]]></description>
		
		
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		<title>Building confidence in a decision</title>
		<link>https://noise.getoto.net/2021/11/15/building-confidence-in-a-decision/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Mon, 15 Nov 2021 16:20:05 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[decision-making]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, Michael Lindon, and Colin McFarlandThis is the fifth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Need to catc...]]></description>
		
		
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		<title>Interpreting A/B test results: false negatives and power</title>
		<link>https://noise.getoto.net/2021/10/26/interpreting-a-b-test-results-false-negatives-and-power/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Tue, 26 Oct 2021 15:45:24 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[decision-making]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarlandThis is the fourth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Need to catch up? Have a lo...]]></description>
		
		
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		<title>Safe Updates of Client Applications at Netflix</title>
		<link>https://noise.getoto.net/2021/10/07/safe-updates-of-client-applications-at-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Thu, 07 Oct 2021 18:23:30 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[Continuous Delivery]]></category>
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		<category><![CDATA[metrics]]></category>
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					<description><![CDATA[By Minal MishraQuality of a client application is of paramount importance to global digital products, as it is the primary way customers interact with a brand. At Netflix, we have significant investments in ensuring new versions of our applications are...]]></description>
		
		
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		<title>Interpreting A/B test results: false positives and statistical significance</title>
		<link>https://noise.getoto.net/2021/10/07/interpreting-a-b-test-results-false-positives-and-statistical-significance/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Thu, 07 Oct 2021 15:11:37 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarlandThis is the third post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Need to catch up? Have a loo...]]></description>
		
		
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		<title>What is an A/B Test?</title>
		<link>https://noise.getoto.net/2021/09/22/what-is-an-a-b-test/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Wed, 22 Sep 2021 15:54:33 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[decision-making]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarlandThis is the second post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. See here for Part 1: Decisi...]]></description>
		
		
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		<title>Decision Making at Netflix</title>
		<link>https://noise.getoto.net/2021/09/07/decision-making-at-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Tue, 07 Sep 2021 15:47:48 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[decision-making]]></category>
		<category><![CDATA[experimentation]]></category>
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					<description><![CDATA[Martin Tingley with Wenjing Zheng, Simon Ejdemyr, Stephanie Lane, and Colin McFarlandThis introduction is the first in a multi-part series on how Netflix uses A/B tests to make decisions that continuously improve our products, so we can deliver more jo...]]></description>
		
		
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		<title>A Day in the Life of an Experimentation and Causal Inference Scientist @ Netflix</title>
		<link>https://noise.getoto.net/2021/03/03/a-day-in-the-life-of-an-experimentation-and-causal-inference-scientist-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Wed, 03 Mar 2021 00:45:43 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[causal-inference]]></category>
		<category><![CDATA[Data Science]]></category>
		<category><![CDATA[experimentation]]></category>
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					<description><![CDATA[Stephanie Lane, Wenjing Zheng, Mihir TendulkarSource credit: NetflixWithin the rapid expansion of data-related roles in the last decade, the title Data Scientist has emerged as an umbrella term for myriad skills and areas of business focus. What does t...]]></description>
		
		
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		<title>Key Challenges with Quasi Experiments at Netflix</title>
		<link>https://noise.getoto.net/2020/09/02/key-challenges-with-quasi-experiments-at-netflix/</link>
		
		<dc:creator><![CDATA[Netflix Technology Blog]]></dc:creator>
		<pubDate>Tue, 01 Sep 2020 21:54:58 +0000</pubDate>
				<category><![CDATA[ab-testing]]></category>
		<category><![CDATA[Data Science]]></category>
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					<description><![CDATA[Kamer Toker-Yildiz, Colin McFarland, Julia GlickAt Netflix, when we can’t run A/B experiments we run quasi experiments! We run quasi experiments with various objectives such as non-member experiments focusing on acquisition, member experiments focusing...]]></description>
		
		
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