Machine Learning meets Embedded Development {On-demand webinar}
Qt and Ekkono are working together to improve machine learning integration in the embedded development space. Ekkono has its own SDK, built to help developers rapidly deploy edge machine learning to embedded connected devices, allowing for conscious, self-learning, and predictive software. Imagine if all this functionality was easily adaptable into your existing Qt workflows. The possibilities are mind-boggling.
In this webinar you will learn how:
• Ekkono and Qt are paving the way for a streamlined method to implement a machine learning model for anomaly detection within a Qt application
• Improve workflows between machine learning experts and embedded stakeholders (UI/UX + Product managers + Embedded developers)
• Learn how the integration between Ekkono's machine learning for the Edge and Qt framework provides a faster iteration and prototyping procedure for all stakeholders in the embedded space (machine learning experts, embedded developers, UI/UX experts
Oh, here is more
Webinar: How to 10x Development Speed when Building an ADAS HMI Towards Production
Surround Reality (SR) is rapidly gaining traction because it provides the situational awareness toda...
Watch VideoWebinar: Safe, Smart, Seamless: Navigating HMI Hurdles in Lab Equipment
This webinar is part of a two-part series that explores how medical Human–Machine Interfaces (HMIs) ...
Watch VideoWebinar: Qt for MCUs vs. LVGL: A Comparative Study from Design to Deployment
Listen to Qt Group and Spyrosoft for a practical comparison of Qt for MCUs vs. LVGL. See real-world ...
Watch VideoWebinar: Leading into 2026: Insights for the Software-Defined Vehicle era
The software-defined vehicle (SDV) era isn’t coming, it’s already here. But this shift is creating a...
Watch Video