Automating Machine Learning and Deep Learning Workflows
summary
Shows how to automate iterative ML and deep learning workflows using Polyaxon on Kubernetes, covering steps like dataset creation, post-processing, augmentation, modeling, prediction and deployment. Demonstrates automating repetitive pipelines and applying advanced techniques such as feature selection and hyperparameter optimization to make experiments reproducible, scalable and portable.
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