Amazon Rekognition is an out-of-the-box machine learning platform for image and video analysis. Here’s a closer look at what it can do.
How do you go about exploring its potential and deciding if there is anything to it? Here’s our step-by-step guide using a real life example.
How can you increase conversion rates for an e-commerce site using a recommendation engine when your users are unidentified?
Joel Jamieson – Principal Delivery Lead at DiUS – reflects on his experience helping Black Dog Institute create a suicide prevention app…
Our long-time friends at Code Like a Girl have really come to the table this holiday season with this gender neutral list of top toys to help kiddos grow their STEM skills.
We’ve used AWS IoT Core so many times on an embedded Linux device, we created an open source service to reduce implementation effort . Dubbed chariotd and written in NodeJS, its a very useful and a lean implementation that provides access to key AWS IoT Core features – Device Shadow handling, MQTT message publishing and Fleet Provisioning.
We often get brought on board to help productise ‘IoT’ (that’s Internet of Things, if you have somehow managed to escape the acronym) devices, and depending on the domain it’s often a Linux based device. Something we commonly see is that developers who are entering the embedded Linux space from the server or desktop direction are carrying over patterns from there out of habit.
You may have heard the somewhat alarming term ‘post-truth era’ in the headlines recently, and along with it the uprising of fake news. So, where did the truth go and what made it disappear? Is social media to blame? And what does this mean for us as Experience Designers?
A few weeks ago, I was given the opportunity to participate in a GameDay on a client engagement. As this would be my first Gameday, I was super excited, however I had little idea about what to expect, or how I should prepare for it. In this blog post, I’ll share my own personal experience from participating in a GameDay, with a focus on the more technical side of things.
As specialists in helping organisations navigate new areas of tech, we wanted to share what we’ve learnt about how to successfully productionise ML projects. The practical points discussed here will benefit ML specialists and consultants, MLOps and project managers or software developers who are involved in productionising ML projects.