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Submit ReviewMachine learning model research requires running expensive, long-running experiments where even a slight mis-calibration can cost millions of dollars in underutilized compute resources. Once trained, model deployment, production monitoring, and observability requirements all present unique operational challenges. Chris Van Pelt is the Chief Information Officer of Weights and Biases, which is the industry standard in
The post Weights & Biases with Chris Van Pelt appeared first on Software Engineering Daily.
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Machine learning model research requires running expensive, long-running experiments where even a slight mis-calibration can cost millions of dollars in underutilized compute resources. Once trained, model deployment, production monitoring, and observability requirements all present unique operational challenges.
Chris Van Pelt is the Chief Information Officer of Weights and Biases, which is the industry standard in experiment monitoring and visualization, and has expanded that expertise into a comprehensive suite of ML Ops tooling including model management, deployment, and monitoring.
3-2.png">3-2.png?resize=218%2C258&ssl=1" alt="" width="218" height="258">Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from information visualization to quantum computing. Currently, Sean is Head of Marketing and Developer Relations at Skyflow and host of the podcast Partially Redacted, a podcast about privacy and security engineering. You can connect with Sean on Twitter @seanfalconer .
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