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Building Efficient PyTorch Models on Vertex AI
Originally aired:
About the Session
It is widely understood that for model training with large amounts of data, using the distributed training paradigm and reading data from cloud storage is the best practice.
In this talk, we walk through methods to improve training performance distributed training paradigms with data on cloud and appropriate data formats, attendees will learn how to build efficient PyTorch models on Google Cloud Vertex AI and will discover how to train PyTorch models with prebuilt or custom containers, perform distributed training, and tune hyperparameters. We'll also explore how to deploy PyTorch models on Vertex AI and orchestrate ML workflows for PyTorch models on Vertex AI pipelines and build PyTorch inference pipelines with Cloud Dataflow, enabling scalable and efficient processing of large volumes of data.
This session will provide practical insights and strategies to help ML Engineers build and deploy efficient PyTorch models on GCP using Vertex AI.
Building Efficient PyTorch Models on Vertex AI
Originally aired:
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