Build/Train/Deploy Machine Learning Models

  • Prepare your Datasets at Scale using Apache Spark and SageMaker Data Wrangler [Level 300]34:11

    Prepare your Datasets at Scale using Apache Spark and SageMaker Data Wrangler [Level 300]

    Discover ways to use Apache Spark on AWS to analyze large datasets, perform data quality checks, transform raw data into machine learning features, and train predictive models.

    Watch Session »
  • Orchestrate and Automate Machine Learning Workflows with SageMaker Pipelines [Level 300]34:51

    Orchestrate and Automate Machine Learning Workflows with SageMaker Pipelines [Level 300]

    In this session, you'll see how to create, automate, and manage end-to-end ML workflows using Amazon SageMaker Pipelines.

    Watch Session »
  • Comparing Models in Production with Multi-Armed Bandits and Reinforcement Learning [Level 300]36:09

    Comparing Models in Production with Multi-Armed Bandits and Reinforcement Learning [Level 300]

    Using the popular Hugging Face Transformers open source library for BERT to train and deploy multiple natural language understanding (NLU) models.

    Watch Session »
  • Reduce Training Time and Cost with SageMaker Debugger  [Level 300]34:33

    Reduce Training Time and Cost with SageMaker Debugger [Level 300]

    In this session, we walk through how to use the real-time training metrics and set up alerts so you can reduce troubleshooting time, training costs and improve model quality.

    Watch Session »
  • Standardize and Automate your Feature Engineering Workflows with SageMaker Feature Store [Level 300]39:45

    Standardize and Automate your Feature Engineering Workflows with SageMaker Feature Store [Level 300]

    Learn how to solve all these problems with Amazon SageMaker Feature Store, and how to use it with both the SageMaker Studio user interface and the SageMaker SDK.

    Watch Session »
  • AWS Innovate: AI/ML Edition

    Home »
  • loading
    Loading More...