11 min listen
Stealing Models from the Cloud
FromData Skeptic
ratings:
Length:
37 minutes
Released:
Oct 28, 2016
Format:
Podcast episode
Description
Platform as a service is a growing trend in data science where services like fraud analysis and face detection can be provided via APIs. Such services turn the actual model into a black box to the consumer. But can the model be reverse engineered? Florian Tramèr shares his work in this episode showing that it can. The paper Stealing Machine Learning Models via Prediction APIs is definitely worth your time to read if you enjoy this episode. Related source code can be found in https://github.com/ftramer/Steal-ML.
Released:
Oct 28, 2016
Format:
Podcast episode
Titles in the series (100)
[MINI] type i / type ii errors: In this first mini-episode of the Data Skeptic Podcast, we define and discuss type i and type ii errors (a.k.a. false positives and false negatives). by Data Skeptic