Karl is a Manager of Cloud AI Advocacy at Google, based in Austin, TX. He leads a global team of data science and engineering experts who engage with users at events, build impactful content, and influence Google product strategy. Previously, he was Director of Engineering at SparkCognition, where he led cross-functional teams that included building an ML-based malware detection.
Karl holds a BS in Computer Science from Duke University, and an MBA from the University of Texas – Austin.
AutoML enables you to create high-quality custom machine learning models without being an ML expert. Leveraging neural architecture search technology, it will automate the process of model selection, tuning, and training in the cloud. In this session, you’ll learn more about how AutoML works and how to apply it to structured data, images, and text.
1. What AutoML is and how it works
2. How can AutoML help both new and experienced data scientists
3. How to apply AutoML to various types of problems to build a model
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