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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 25 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: One of the most consistent challenges for ML engineers is how to move from model to production. Join us for a day of sessions dedicated to making the most of AI in your company. You’ll learn about everything from scaling to deployment and from pipeline to model decay—straight from our experts. About the AI Superstream Series: This four-part series of half-day online events is packed with insights from some of the brightest minds in AI. You’ll get a deeper understanding of the latest tools and technologies that can help keep your organization competitive, and learn to leverage AI to drive real business results. What you'll learn-and how you can apply it Understand how MLOps can help you evolve from manually building models Learn how to use PyTorch to effectively deploy and scale your AI models Explore design patterns that will help you tackle problems that frequently crop up during the ML process This Superstream is for you because... You want to learn more about moving machine learning from model to production. You want to better understand MLOps. You’re interested in improving your skills in scaling, model monitoring, and deployment. Prerequisites Come with your questions Have a pen and paper handy to capture notes, insights, and inspiration
    Note: Online resource; Title from title screen (viewed March 17, 2021) , Mode of access: World Wide Web.
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  • 2
    ISBN: 9781098159191 , 1098159195
    Language: English
    Pages: 1 online resource
    Edition: First edtion.
    Parallel Title: Erscheint auch als
    DDC: 006.3
    Keywords: Amazon Web Services (Firm) ; Artificial intelligence Computer programs ; Application software
    Abstract: Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock.
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