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Skip to main contentAWS Startups

    Deploying DeepSeek V3 and DeepSeek-R1 on Amazon SageMaker

    AI

    AWS Startups

    Generative AI

    Machine Learning

    SageMaker

    Technical

    Day:

    Thursday, February 6, 2025

    Time:

    4:30 AM - 10:30 AM GMT

    Type:

    IN PERSON

    Speakers:

    Supreeth S Angadi | GenAI/ML Startups Solution Architect, AWS, Pradipta Dash | Senior Startups Solutions Architect, AWS, Sourabh Jain | Sr. GenAI Startups Account Manager, AWS

    Language:

    English

    Capacity:

    Full - This event is at capacity

    Level(s):

    300 - Advanced, 400 - Expert

    Are you a startup founder or machine learning (ML) engineer looking to effectively deploy and manage AI models while optimizing costs?

    Join us for an intensive hands-on workshop exploring Amazon SageMaker Studio's unified ML development environment and learn production-ready strategies for model deployment.

    DeepSeek is a cutting-edge family of large language models that has gained significant attention in the AI community for its impressive performance, cost-effectiveness, and open-source nature. DeepSeek offers a range of models including the powerful DeepSeek-V3, the reasoning-focused DeepSeek-R1, and various distilled versions. These models stand out for their innovative architecture, utilizing techniques like Mixture-of-Experts and Multi-Head Latent Attention to achieve high performance with lower computational requirements.

    In this hands-on workshop, you'll learn about Amazon SageMaker Studio's comprehensive toolkit to self-host large language models from DeepSeek while maintaining cost efficiency.

    Who is this for? This workshop is ideal for:

    • Startup founders and technical leaders creating AI solutions
    • ML Engineers and Data Scientists
    • DevOps professionals managing GenAI/ML infrastructure
    • Technical decision-makers evaluating GenAI/ML platforms
    • Developers interested in self-hosting open-source LLMs
    • Engineers looking to optimize their GenAI/ML infrastructure costs

    During this hands-on workshop, you'll learn how to leverage Amazon SageMaker Studio's unified environment to streamline your ML workflows and implement cost-effective model deployment strategies.

    Key highlights:

    • Master Amazon SageMaker Studio's unified interface and development environment
    • Hands-on implementation of self-hosting DeepSeek and similar models
    • Deploy cost-optimization strategies including scale-to-zero capabilities
    • Enhance inference performance using Fast Model Loader and container caching
    • Best practices for managing GenAI/ML development lifecycle
    • Real-world examples of production GenAI/ML infrastructure optimization
    • Interactive troubleshooting and optimization sessions

    This workshop is specifically designed for startup teams who want to productionze GenAI/ML infrastructure while maintaining cost efficiency. You'll gain hands-on experience with Amazon SageMaker's advanced features and learn practical strategies for managing GenAI/ML workloads.


    Prerequisites:

    • Laptop with adequate specifications for hands-on exercises
    • Basic understanding of machine learning concepts
    • Familiarity with Python programming
    • AWS account access
    • Basic knowledge of container technologies
    • Understanding of ML deployment concepts.

    By registering, you agree to the AWS Event Terms & Conditions and AWS Code of Conduct.