From 39614b0317bb9d287548dbaec5ea2f3d5b6b80f6 Mon Sep 17 00:00:00 2001 From: Frederick Legaspi Date: Mon, 6 Dec 2021 10:21:06 -0500 Subject: [PATCH] Fix typo Fix minor typo --- 6-Data-Science-In-Wild/20-Real-World-Examples/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/6-Data-Science-In-Wild/20-Real-World-Examples/README.md b/6-Data-Science-In-Wild/20-Real-World-Examples/README.md index 098a389..b3dcdd3 100644 --- a/6-Data-Science-In-Wild/20-Real-World-Examples/README.md +++ b/6-Data-Science-In-Wild/20-Real-World-Examples/README.md @@ -26,7 +26,7 @@ Thanks to the democratization of AI, developers are now finding it easier to des * [Sports Analytics](https://towardsdatascience.com/scope-of-analytics-in-sports-world-37ed09c39860) - focuses on _predictive analytics_ (team and player analysis - think [Moneyball](https://datasciencedegree.wisconsin.edu/blog/moneyball-proves-importance-big-data-big-ideas/) - and fan management) and _data visualization_ (team & fan dashboards, games etc.) with applications like talent scouting, sports gambling and inventory/venue management. - * [Data Science in Banking](https://data-flair.training/blogs/data-science-in-banking/) - highlights the value of data science in the finance industry with applications ranging from risk modeling and fraud detction, to customer segmentation, real-time prediction and recommender systems. Predictive analytics also drive critical measures like [credit scores](https://dzone.com/articles/using-big-data-and-predictive-analytics-for-credit). + * [Data Science in Banking](https://data-flair.training/blogs/data-science-in-banking/) - highlights the value of data science in the finance industry with applications ranging from risk modeling and fraud detection, to customer segmentation, real-time prediction and recommender systems. Predictive analytics also drive critical measures like [credit scores](https://dzone.com/articles/using-big-data-and-predictive-analytics-for-credit). * [Data Science in Healthcare](https://data-flair.training/blogs/data-science-in-healthcare/) - highlights applications like medical imaging (e.g., MRI, X-Ray, CT-Scan), genomics (DNA sequencing), drug development (risk assessment, success prediction), predictive analytics (patient care & supply logistics), disease tracking & prevention etc.