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There are many possible ways of event handling. Choosing the wrong one for your needs can be a serious mistake. This article shows you some of the choices available and trade-offs you have to consider with each of them. Some are related to Elixir itself, and some are technology-agnostic.
Training a neural network for image and video classification often requires multiple steps. First, you annotate images and frames with bounded-boxes, polygons, skeletons, and many other formats. The annotations are then labeled and used to train computer vision models. Labeled annotations are also used to verify models against biases, outliers, and over/underfitting.
The goal of this post is to focus on the current state of some projects in the ecosystem and then briefly highlight a few of the exciting efforts coming over the next months.
As We run almost all our work loads in containers we take advantage of the same build pipelines for building container images to run CI/CD as well. Elixir runs on BEAM and has some nice features such as hot redeploys that is something anti to the concept of containers where they are immutable images none the less it does not mean Elixir is not container friendly.
Kevala is looking for an experienced senior/prinicipal (Elixir) software engineer to help design and build a modern healthcare workforce orchestration platform. This is an opportunity to build a new product from the ground up. You will be working directly with a battle-tested founding team during the early stages of a growing startup.