From bf43fbd5b9bc7fc804e5189c943bb76cc06774cc Mon Sep 17 00:00:00 2001 From: Minsuk Choi Date: Fri, 1 Oct 2021 12:23:32 +0900 Subject: [PATCH] Unify company name: NetFlix -> Netflix --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 442cdc9..4af68e3 100644 --- a/README.md +++ b/README.md @@ -124,7 +124,7 @@ P.P.S, Looking for guides and interviews on applying ML? 👉[`applyingML`](http ## Regression 1. [Using Machine Learning to Predict Value of Homes On Airbnb](https://medium.com/airbnb-engineering/using-machine-learning-to-predict-value-of-homes-on-airbnb-9272d3d4739d) `Airbnb` 2. [Using Machine Learning to Predict the Value of Ad Requests](https://blog.twitter.com/engineering/en_us/topics/insights/2020/using-machine-learning-to-predict-the-value-of-ad-requests.html) `Twitter` -3. [Open-Sourcing Riskquant, a Library for Quantifying Risk](https://netflixtechblog.com/open-sourcing-riskquant-a-library-for-quantifying-risk-6720cc1e4968) ([Code](https://github.com/Netflix-Skunkworks/riskquant)) `NetFlix` +3. [Open-Sourcing Riskquant, a Library for Quantifying Risk](https://netflixtechblog.com/open-sourcing-riskquant-a-library-for-quantifying-risk-6720cc1e4968) ([Code](https://github.com/Netflix-Skunkworks/riskquant)) `Netflix` 4. [Solving for Unobserved Data in a Regression Model Using a Simple Data Adjustment](https://doordash.engineering/2020/10/14/solving-for-unobserved-data-in-a-regression-model/) `DoorDash` ## Forecasting