Can anyone recommend best practices for deploying/configuring a data loss prevention platform? How do you make sure you're minimizing false positives/negatives, getting accurate detection, etc?

A lot of people will give you a set of tools and processes to ensure DLP effectiveness. A different perspective is to ensure you have you data classification done right and in a way that can be maintained. The more fine grained you can get the less false positives. There are tools that vendors claim that have “AI” for detection but without classification any AI won’t be effective or efficient. There is no AI that I know of that can substantially make a dent in classification of data beyond identification of PII etc. In other words there are precursors to DLP beyond configuration that need to happen to make your detection effective.

I like Microsoft Purview Data Loss Prevention, it works well with Microsoft systems, Networks, emails, etc.
https://www.gartner.com/reviews/market/data-loss-prevention/vendor/microsoft/product/microsoft-purview-data-loss-prevention

I would recommend this : https://start.paloaltonetworks.com/modern-enterprise-dlp-facilitating-gdpr?utm_source=google-jg-amer-sase&utm_medium=paid_search&utm_term=data%20loss%20prevention%20best%20practices&utm_campaign=google-sase-casb-amer-multi-lead_gen-en-eg&utm_content=gs-20039126345-154114646568-656502004727&sfdcid=7014u000001ZAovAAG&gclid=CjwKCAjw8symBhAqEiwAaTA__C85Q42RrbIh8Ps8JPIgKheCHIkBB4aDOSZeYnlBBPXAUImTL2y8JRoCZZ8QAvD_BwE