Journey of a datascience feature - Start to End (still Work in Progress) Key Takeaway - Its fine to be not 100% accurate, roll it out and learn. tl;dr - Appr

Journey of a datascience feature - Start to End (still Work in Progress) Key Takeaway - Its fine to be not 100% accurate, roll it out and learn. tl;dr - Approval from Execs - Data -> Learning -> Training -> Variability -> Training -> Tuning - Privacymatters (for all digital educated , uneducated) - What & Whys of UX -- ultimately what user says - Definitely Cloud -- Its 21st Century - Optimised for Speed , Cost (a bit irrelevant if I am Google ;) ) - Release (with presentation) -- Timing matters - Feedbacks (On permission) A summary on the "Denoiser" and not "Noise cancellation" [Don't want to get ranted out by Data Science folks] feature of googlemeet by PM. Applies to any such feature.