David is an AI/ML Engineer at DigitalOcean, where he’s dedicated to empowering developers to build, scale, and deploy AI/ML models in production environments. David brings deep expertise in building and training models for applications like NLP, data visualization, and real-time analytics. His mission is to help users build, train, and deploy AI models efficiently, making advanced machine learning accessible to developers of all levels.

I also have a background in storage drivers/firmware/management, backup and recovery solutions for virtualized environments, I'm a contributor to Kubernetes and many Cloud Native Computing Foundation (CNCF) projects, and backup/recovery solutions, etc! Please reach out and ask me anything!

Open Source Contributions: http://www.github.com/davidvonthenen

Follow me on Twitter: http://www.twitter.com/dvavidonthenen

LinkedIn: https://linkedin.com/in/davidvonthenen

Blog: https://davidvonthenen.com

Presentations

22x

Training Multi-Modal ML Classification Models for Real-Time Detection of Debilitating Disease

This session breaks down the training process of multi-modal machine learning models for real-time detection of debilitating diseases using video and audio data. Attendees will learn how to build and integrate video and audio classifiers, curate multi-modal datasets, and deploy these models in real-world settings. The session includes practical demonstrations and code samples to help participants implement their own multi-modal classification models, equipping them with tools and methodologies to apply in the healthcare industry or other fields requiring complex real-time detection.

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21x

Voice-Activated AI Collaborators: A Hands-On Guide Using LLMs in IoT & Edge Devices

Discover the power of voice-assisted IoT and Edge interfaces in this practical session. Learn to create effective voice-activated devices, using LLMs like Falcon and OpenLLaMA. Gain insights into design decisions, essential components, and collaborative frameworks.

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16x

Application Monitoring and Tracing in Kubernetes: Avoiding Microservice Hell!

Creating and deploying Microservices is easy. The real problem is how to manage and support these services out in the wild and in production. What happens when these services stop working or worse yet when they are running but running slowly? Which service instance is the culprit? This session talks about how you can leverage Jaeger, OpenTracing, and Prometheus in order to give better visibility into the distributed nature of a Microservice architecture in a Kubernetes environment.

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15x

How Container Schedulers and Software Defined Storage will Change the Cloud

Persistent applications can be complex to manage and operate at scale, but tend to be perfect for modern schedulers such as Apache Mesos, Kubernetes, and etc. Internal direct attached storage and external storage are both options to run your applications. This talk outlines how 2 Layer Scheduling and Software Defined Storage enables deployment of managed frameworks and tasks, while maintaining high availability, scale-out growth, and automation.

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