Building Scalable End-to-End Deep Learning Pipelines in the Cloud

Explore serverless deep learning on AWS in this 15-minute conference talk. Learn how to leverage AWS Batch, Fargate, SageMaker, Lambda, and Step Functions to create scalable and cost-effective deep learning pipelines. Discover the benefits of adopting a serverless approach for machine and deep learning projects, focusing on simplified architecture and model-centric development. Gain insights into overcoming challenges in training and operationalizing models within a company's framework. Understand the limitations and organizational strategies for model training and deployment in a serverless environment. See how this approach can revolutionize deep learning projects by prioritizing model development and operational efficiency.

Building scalable end-to-end deep learning pipelines in the cloud - Rustem Feyzkhanov