What is Differential Privacy and Why Does it Matter?
At a time when the risks and costs associated with privacy are on the rise, differential privacy offers a solution. Differential privacy is mathematical definition for the privacy loss that results to individuals when their private information is used to create an AI product. It can be used to build customer trust, making those customers more likely to share their data with you. This slideshare will help you get a concise explanation of what differential privacy is, how it works, and how you can use it to help your company improve your machine learning models and overcome the cold-start problem.