How Showmax got into live streaming
Part II - Sometimes the only way is the way of The Force
In the first part of this series, we explained how Showmax got into the live streaming business and the problems we faced while developing our redundant setup. Now, the fun stuff - here’s a little dive into why our live encoding checker was sometimes... »
How Showmax got into live streaming
Part I - Adventures in achieving streaming redundancy
This is the first in a series of articles about how Showmax made a radical departure from its video-on-demand roots and took a live streaming platform from scratch to production in less than three months. In particular, we’ll share some of the key... »
Looking for a Django Admin Page Lock? We've got you covered
One of the main projects that my team is responsible for is Showmax’s CMS (Content Management System), where we manage content metadata for our streaming platform through their browsers. The CMS is used by multiple users in five different countries... »
Implementing GraphQL API In The Browser
This September, I gave a talk at WebExpo Prague explaining why and how we used GraphQL to reduce data fetching and improve the UI of the Showmax Video on Demand platform. I’ve put together some more technical details in this article so you can try... »
State of Deep Learning in Computer Vision
Part II - The Attention Mechanism
This article is an extension of a talk I gave at the Czech Technical University (CTU) in July 2017. We surveyed around a hundred deep learning papers and selected the most interesting and important outcomes that will help you to understand the impact of deep learning in computer vision. Our talk touched on three topics: novel architectures of Convolutional Neural Networks (ConvNets), the Attention Mechanism, and Video Classification. These are the most critical components of our deep learning system. We use these at the ShowmaxLab at CTU to better understand movies. This is the second of two parts focused on Attention. If you have not already, please check the first article about ConvNet Architectures. »
State of Deep Learning in Computer Vision
Part I - ConvNet Architectures
This article is an extension of a talk I gave at the Czech Technical University (CTU) in July 2017. We surveyed around a hundred deep learning papers and selected the most interesting and important outcomes that will help you to understand the impact of deep learning in computer vision. Our talk touched on three topics: novel architectures of Convolutional Neural Networks (ConvNets), the Attention Mechanism, and Video Classification. These are the most critical components of our deep learning system. We use these at the ShowmaxLab at CTU to better understand movies. This is the first of two parts focused on ConvNets, the second one will cover the Attention. »