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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. The sessions showcase how Amazon Q can help you streamline coding, testing, and troubleshooting, as well as enable you to make the most of your data to optimize business operations.

AWS 108
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Top 10 Deep Learning Platforms in 2024

DagsHub

TensorFlow The Google Brain team created the open-source deep learning framework TensorFlow, which was made available in 2015. Developed by François Chollet, it was released in 2015 to simplify the creation of deep learning models. Further Reading and Documentation H2O.ai Documentation H2O.ai

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Why is Git Not the Best for ML Model Version Control

The MLOps Blog

Starting from AlexNet with 8 layers in 2012 to ResNet with 152 layers in 2015 – the deep neural networks have become deeper with time. It requires significant effort in terms of data preparation, exploration, processing, and experimentation, which involves trying out algorithms and hyperparameters.

ML 52
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Fine-tune Meta Llama 3.2 text generation models for generative AI inference using Amazon SageMaker JumpStart

AWS Machine Learning Blog

Prerequisites To try out this solution using SageMaker JumpStart, you’ll need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. He is specialized in architecting AI/ML and generative AI services at AWS.

AI 123