Making computers identify and understand what they are looking at in digital images is an ongoing challenge. Recent years have seen notable increases in the accuracy and speed of object detection due to deep learning and new applications of neural networks. In order to make it easier for developers to take advantage of these techniques Tryo Labs built Luminoth. In this interview Joaquín Alori explains how how Luminoth works, how it can be used in your projects, and how it compares to API oriented services for computer vision.

Do you want to try out some of the tools and applications that you heard about on Podcast.__init__? Do you have a side project that you want to share with the world? With Linode’s managed Kubernetes platform it’s now even easier to get started with the latest in cloud technologies. With the combined power of the leading container orchestrator and the speed and reliability of Linode’s object storage, node balancers, block storage, and dedicated CPU or GPU instances, you’ve got everything you need to scale up. Go to pythonpodcast.com/linode today and get a $60 credit to launch a new cluster, run a server, upload some data, or… And don’t forget to thank them for being a long time supporter of Podcast.__init__!

GoCD is the on-premise open source continuous delivery server created by ThoughtWorks and modeled after the ideas in the Continuous Delivery book by Jez Humble and David Farley.

With GoCD’s comprehensive pipeline modeling, you can model complex workflows for multiple teams with ease. And GoCD’s Value Stream Map lets you track a change from commit to deploy at a glance.

GoCD’s real power is in the visibility it provides over your end-to-end workflow. So you get complete control of and visibility into your deployments, across multiple teams.

Say goodbye to deployment panic and hello to consistent, predictable deliveries.

To learn more about GoCD, visit gocd.org for a free download. Professional Support and enterprise add-ons, including disaster recovery, are available.

Datadog is a powerful, easy to use service for gaining comprehensive visibility into the state of your applications.

The easy to install Python agent lets you collect system metrics and log data, supports integrations with all of your services, and distributed tracing.

Their customizable dashboards and interactive graphs make finding and fixing performance issues fast and easy, and their machine-learning driven alerting ensures that you always know what is happening in your systems. If you need even more detail about how your application is functioning you can track custom metrics, and their Application Performance Monitoring (APM) tools let you track the flow of requests through your stack.