What it takes to build great machine learning products 
A great and insightful article. A common theme I've seen in practice is folks who have a deep understanding of ML often run straight to applying the most sophisticated algorithms possible on raw data. On the other hand, people who know a bit about ML but understand the domain better start by applying intuition to data cleansing and then follow up with simpler algorithms. Without fail the latter group ends up with better results.