AI/Ml Fundamentals, Framework, & Tools

  • Scale your Large Distributed Training Jobs with Data and Model Parallelism Optimized for Amazon SageMaker [Level 300]36:57

    Scale your Large Distributed Training Jobs with Data and Model Parallelism Optimized for Amazon SageMaker [Level 300]

    In this session, explore how to choose the proper instance for ML training and inference based on model size, complexity, throughput, framework choice, inference latency and portability requirements.

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  • Detect Potential Bias in your Datasets and Explain how your Models Predict using SageMaker Clarify (Level 300)33:29

    Detect Potential Bias in your Datasets and Explain how your Models Predict using SageMaker Clarify (Level 300)

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  • Select the Right ML Instance for your Training and Inference Job (Level 300)39:41

    Select the Right ML Instance for your Training and Inference Job (Level 300)

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  • Automate Code Reviews, Performance Recommendations and Operational Insights  (Level 300)44:44

    Automate Code Reviews, Performance Recommendations and Operational Insights (Level 300)

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  • Build Quality ML Models Quickly & Easily with Amazon SageMaker Autopilot (Level 200)36:14

    Build Quality ML Models Quickly & Easily with Amazon SageMaker Autopilot (Level 200)

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  • Deploy State of the Art ML Models and Solutions in a Single Click (Level 200)32:26

    Deploy State of the Art ML Models and Solutions in a Single Click (Level 200)

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  • AWS Innovate: AI/ML Edition

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