Object detection is a very important problem in computer vision due its numerous applications from self-driving cars to security and tracking. In recent years, this field has seen tremendous progress, aided by the advent of deep learning. Today, we’re talking about the You Only Look Once (or YOLO) approach and why it’s the better option compared to other techniques in object detection.
Bayesian Nonparametrics is a class of models with a potentially infinite number of parameters. High flexibility and expressive power of this approach enables better data modelling compared to parametric methods. We have prepared the introduction to Bayesian Nonparametrics: the Dirichlet process along with associated models and links to their implementations.
Did you know that Hillary Clinton has a team of software engineers? We don’t operate at Google scale, but we scale people and products rapidly. We’ve only been around for a year and we’ve accomplished a lot. We have about 50 backend services and 20 frontend applications in production. We have over 237 Git repos. We maintain a query intensive, 15TB data warehouse that services a team of data scientists and analysts. We’ve built a mountain of applications that range in purpose from fundraising to staff tooling to making it easier for grassroots supporters to organize and vote. When I worked on the President’s 2012 reelection campaign we didn’t talk openly about our work. Our technology was a competitive secret and we didn’t want it to be part of the election year narrative. This time we’d like to be more open about some of the things our team is working on. Politics is a democratic sport and we feel that the more our community understands what we’re doing, the more likely they are to participate. So what exactly does a technology team on a presidential campaign do? Whether you're a hillary fan or not, this is an interesting read.
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