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Improving air quality with generative AI

AWS Machine Learning Blog

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. As always, AWS welcomes your feedback.

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Use foundation models to improve model accuracy with Amazon SageMaker

AWS Machine Learning Blog

By utilizing insights found in the images, not previously available in the tabular data, we can improve the accuracy of the model. Both the images and tabular data discussed in this post were originally made available and published to GitHub by Ahmed and Moustafa (2016). How would you assess the home’s value from these images?

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HAYAT HOLDING uses Amazon SageMaker to increase product quality and optimize manufacturing output, saving $300,000 annually

AWS Machine Learning Blog

Input data is streamed from the plant via OPC-UA through SiteWise Edge Gateway in AWS IoT Greengrass. Model training and optimization with SageMaker automatic model tuning Prior to the model training, a set of data preparation activities are performed. Samples are sent to a laboratory for quality tests.

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Around this time, industry observers reported NVIDIA’s strategy pivoting from its traditional gaming and graphics focus to moving into scientific computing and data analytics.

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Top 10 Deep Learning Platforms in 2024

DagsHub

Further Reading TensorFlow Documentation TensorFlow Tutorials PyTorch PyTorch, developed by Facebook's AI Research Lab (FAIR) , was released in 2016. Founded in 2016, HuggingFace has strongly impacted the field of NLP with its easy-to-use APIs and pre-trained models. Further Reading and Documentation H2O.ai Documentation H2O.ai

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Effectively solve distributed training convergence issues with Amazon SageMaker Hyperband Automatic Model Tuning

AWS Machine Learning Blog

arXiv preprint arXiv:1609.04836 (2016). [3] In his spare time, he enjoys cycling, hiking, and complaining about data preparation. International Conference on Machine Learning. PMLR, 2018. [2] 2] Keskar, Nitish Shirish, et al. “On On large-batch training for deep learning: Generalization gap and sharp minima.”

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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.

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