Machine learning18

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Ludovico Bessi

#21 Online serving

Table of contents 1. Introduction. 2. Online predictions with batch features. 3. Online predictions with online features: real time vs near real time. 4. When does it make sense to move things online? Introduction As a follow up of my past article related to Batch Serving: Machine Learning at scale:...

Ludovico Bessi

#16 Robust machine learning models in an adversarial world.

Table of contents 1. Introduction. 2. Adversarial examples and robust classifiers. 3. How to generate adversarial examples. 4. How to defend your precious Machine Learning models against adversarial examples. Introduction Today's article will dive deep into adversarial examples. There are two major reasons adversarial examples are important to understand: 1....

Ludovico Bessi

#15 Near real-time personalization at LinkedIn.

Table of contents 1. Introduction. 2. Past actions affect personalized recommendations with delay. 3. Leveraging actions in near real-time to adapt recommendations. 4. Results. Introduction In today's article, I will talk about LinkedIn transitioned from an offline update to a near real-time update of features for recommender systems that power...

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