A Deep Dive on Text Classification at Salesforce
published on Towards Data Science
We’re excited to announce that Noah Burbank, a Principal Data Scientist in Sales Cloud, has recently published a deep dive into text classification at Salesforce on Towards Data Science. The article, How to choose the right model for text classification in an organizational setting, applies counterintuitive advice from golf to Data Science: you might be better off skipping the sand wedge and using a putter to get out of sand trap.
In the article Noah goes through the technical trade-offs of three different text classification approaches: Regular Expressions, Machine Learning, and Deep Learning. But after the technical deep dive he reveals his key takeaway: the best model isn’t the one with the highest F1-score, the best model is
one that you can deploy with the resources you have, trained with the data you can get, in the amount of time that your boss has patience for
Read the full post on Towards Data Science
If you enjoy the post, you might want to read some of Noah’s other blog posts on the Salesforce Engineering Blog about designing NLP systems or about using open source data to preserve customer privacy.
