The convergence of machine learning and edge AI presents Engineers with unique challenges that require a specialized skill set beyond traditional machine learning engineering. In this webinar you will gain insights into trends and best practices in implementing Machine Learning at the Edge, from optimisation, and deployment to monitoring.

Discover how to: 

🔒 Enhance Data Access, Security and Privacy through Federated Learning with OWKIN and APHERIS

💪 The tools, systems and structures you need to put in place for real-time AI with MODZY and BARBARA

🚀 Improve model performance for Computer Vision with PICSELLIA

⚙️ Run successful Machine Learning Model Inference with SELDON 

💡 Optimize ML models for edge devices with HPE

🔒 Secure your ML models in the edge with NVIDIA

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