Precision tells us how many of the items we identified as correct were actually correct, while recall tells us how many of the correct items we were able to identify. It’s like looking for gold: precision is our accuracy in finding only gold instead of rocks, and recall is our success in finding all the pieces of gold in the dirt.

• Machine learning and data analysis
• Image and speech recognition
• Natural language processing
• Quality control and manufacturing
• Healthcare and medical diagnosis

Let’s say you have a list of 1000 emails and you want to find all the ones that contain the word ‘urgent’ in the subject line. If your precision is 95% but your recall is only 80%, it means you identified 950 emails as having the word ‘urgent’ in the subject line, but you actually found 800 of them. So while you were very accurate in identifying the emails that contained the word ‘urgent’, you missed a lot of them.

• How to measure the success of your data strategy