Justin Patriquin

Conf42: Python 2023

Protecting Sensitive Data and Machine Learning Models

The area where data is being processed and held in memory is nearly always unencrypted and may be at higher risk of cyberattacks. This talk will share how engineers can deploy functions containing proprietary algorithms, models, and secrets while keeping your intellectual property confidential.