Hyper-Personalisation In Retail — 2020 Just imagine knowing that the shirt you ordered online will definitely fit, because you’ve already seen it on your body... in virtual reality!
Machine Learning for 5G – An Opportunity for Mobile Network Operators And Software Houses To Collaborate Although the mobile industry is booming, major Mobile Network Operators didn’t have that many opportunities to collaborate with Software Houses. Until now. Most software used by Mobile Network Operators (MNO), from Customer Experience Management to Core Network Operations, is developed as part of a bigger deal with Radio Access Network…
By Deep Racer to Las Vegas AWS DeepRacer League is a global race where programmable DeepRacers, i.e. autonomous vehicles created by Amazon Web Services (AWS), compete for the title of the fastest. The winner is the first one to learn to overcome obstacles faced along the route. Can you get to Las Vegas by this vehicle? It turns out you can.
Top 5 Reasons To Use Mesh Twin Learning in Your Smart Factory All the world’s talking about Digital Twin – but let’s think a little further ahead than that. Digital Twin is just the first step, not the end destination. Mesh Twin Learning is the next phase – so let’s explore that and provide a number of key benefits that MTL is…
More Effective Machine Learning Production with MLOps Machine Learning is slowly starting to mature as a field, but many businesses are still facing tough upfront challenges. While there are a huge (and increasing) amount of new algorithms, neural network architectures and libraries, practical deployments are still in the toddler phase. However, there’s plenty of new hope for…
Digital Twin: The First Step To Industry 4.0 In one of our recent posts, we introduced the Mesh Twin Learning (MTL) concept, which uses modern technologies to give industrial companies a competitive advantage by introducing micro-optimisations and sharing learned successes across the organisation. MTL is pretty advanced concept, though. It requires data from IoT sensors, the creation of…
MLflow: Tracking ML Model Changes & Deployment in Azure In this post, we’ll cover tracking changes, as well as comparing and tracking the deployment of Machine Learning models using MLflow library. We’ll later set up resources in the Azure Cloud so we can provision our model, as well as create the Azure DevOps pipeline to deploy a new model…
