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Pretrain Vision and Large Language Models in Python(Paperback) : End-to-end techniques for building and deploying foundation models on AWS
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ÀúÀÚ Webber, Emily
ÃâÆÇ»ç/¹ßÇàÀÏ Packt Publishing / 2023.05.31
ÆäÀÌÁö ¼ö 258 page
ISBN 9781804618257
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Part 1: Before Pretraining 1 An Introduction to Pretraining Foundation Models 2 Dataset Preparation: Part One 3 Model Preparation Part 2: Configure Your Environment 4 Containers and Accelerators on the Cloud 5 Distribution Fundamentals 6 Dataset Preparation: Part Two, the Data Loader Part 3: Train Your Model 7 Finding tne Right Hyperparameters 8 Large-Scale Training on SageMaker 9 Advanced Training Concepts Part 4: Evaluate Your Model 10 Fine-Tuning and Evaluating 11 Detecting, Mitigating, and Monitoring Bias 12 How to Depoloy Your Model Part 5: Deploy Your Model 13 Prompt Engineering 14 MLOps for Vision and Language 15 Future Trends in Pretraining Foundation Models Index Other Books You May Enjoy

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Webber, Emily
Emily Webber is a Principal Machine Learning Specialist Solutions Architect at Amazon Web Services. She has assisted hundreds of customers on their journey to ML in the cloud, specializing in distributed training for large language and vision models. She mentors Machine Learning Solution Architects, authors countless feature designs for SageMaker and AWS, and guides the Amazon SageMaker product and engineering teams on best practices in regards around machine learning and customers. Emily is widely known in the AWS community for a 16-video YouTube series featuring SageMaker with 160,000 views, plus a Keynote at O'Reilly AI London 2019 on a novel reinforcement learning approach she developed for public policy.

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