Machine learning is finding
its way in many core business principles but one challenge is the end buyer’s /
customer's confidence in validation, accuracy and fit of the model to predict
and optimize key business functions.
I have worked on tech M&A transactions to perform due diligence for machine learning products and understand these will bring a facelift to traditional enterprise software.
There are workarounds to assess the fit of a traditional model but how do we deliver value and confidence on a real time SaaS machine learning product for accuracy?
We understand customer testimony & past work do make a difference but we are looking for inputs on a sales pitch for prediction & accuracy of the ML model.
Any suggestions, comments, criticism are welcome.