Some weeks ago during a security training for developers provided by Marcus from Hackmanit (by the way, it’s a very good course that goes in some topics since web development until vulnerabilities of NoSQL and some defensive coding) we discussed about some white box attacks in web applications (e.g.attacks where the offender has internal access in the object) I got a bit curious to check if there’s some similar vulnerabilities in ML models. After running a simple script based in ,, using Scikit-Learn, I noticed there’s some latent vulnerabilities not only in terms of objects but also in regarding to have a proper security mindset when we’re developing ML models. But first let’s check a simple example.
Most of the time we completely rely in the default parameters of Machine Learning Algorithm and this fact can hide that sometimes we can make wrong statements about the ‘efficiency’ of some algorithm.
In the post called Learning Market Dynamics for Optimal Pricing post of Sharan Srinivasan he talks about how AirBnb uses ML and Structural Modeling (Mathematical + Statistical Modelling) combined to get some results about the offer to guests the optimal pricing based in market dynamics based in the anticipation of the booking and the difference the time between the booking date until the check-in (also know as Lead Time).
This Michael Kaminsky post called The Blacker the Box nail the whole point about understandability x formal modelling using the speed of feedback as a mechanism to help to decide the best approach to implement these models.
The best musing about machine learning of this week comes from Benedict Evans: Washing machines are robots, but they’re not ‘intelligent’.
In the few months that I arrived in Movile, I saw some strange pattern about several “data analysis”.
From whom are looking an initial approach to know the best time to bill your customers for some subscription services, this paper can be a good start.
Uma das melhores coisas que podem acontecer quando há uma expectativa muito grande em sua área de atuação em tecnologia é quando alguém muito conhecido tem uma mesma opinião de empirismo cético a cerca do estado da arte.