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Dive into a comprehensive 3-hour 47-minute workshop session that guides you through the entire machine learning journey, from concept to production. Learn from industry experts Chanchal Chatterjee, Elvin Zhu, and Timothy Ma as they present an open-source Python template for building and deploying ML components. Explore hands-on tutorials covering data preparation, model hyper-training, model training, deployment, and online/batch prediction. Gain practical experience in unit testing ML components using Python notebooks and discover how to implement these components in a Kubeflow pipeline with orchestration for training and prediction. By the end of this workshop, acquire the skills to build a production-ready ML pipeline using Google Cloud Platform, incorporating models such as XGBoost and TensorFlow.
