Four short links: 3 February 2017
Stream Alerting, Probabilistic Cognition, Migrations at Scale, and Interactive Machine Learning
- StreamAlert — a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Open source from AirBnB.
- Probabilistic Models of Cognition — we explore the probabilistic approach to cognitive science, which models learning and reasoning as inference in complex probabilistic models. In particular, we examine how a broad range of empirical phenomena in cognitive science (including intuitive physics, concept learning, causal reasoning, social cognition, and language understanding) can be modeled using a functional probabilistic programming language called Church.
- Online Migrations at Scale — In this post, we’ll explain how we safely did one large migration of our hundreds of millions of Subscriptions objects. This is a solid process.
- Interactive Machine Learning (Greg Borenstein) — intro to, and overview of, the field of Interactive Machine Learning, elucidating the principles for designing systems that let humans use these learning systems to do things they care about. In Greg’s words, Machine learning has the potential to be a powerful tool for human empowerment, touching everything from how we shop to how we diagnose disease to how we communicate. To build these next thousand projects in a way that capitalizes on this potential, we need to learn not just how to teach the machines to learn but how to put the results of that learning into the hands of people.