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QR codes in AI and ML: Enhancing predictive analytics for business

Dataconomy

In the field of AI and ML, QR codes are incredibly helpful for improving predictive analytics and gaining insightful knowledge from massive data sets. Some of the methods used in ML include supervised learning, unsupervised learning, reinforcement learning, and deep learning.

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Deploy Gradio Apps on Hugging Face Spaces

PyImageSearch

Hugging Face Spaces is a platform for deploying and sharing machine learning (ML) applications with the community. It offers an interactive interface, enabling users to explore ML models directly in their browser without the need for local setup. Or requires a degree in computer science? Thats not the case.

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Map Earth’s vegetation in under 20 minutes with Amazon SageMaker

AWS Machine Learning Blog

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. SageMaker Processing provisions cluster resources for you to run city-, country-, or continent-scale geospatial ML workloads.

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Introducing Fast Model Loader in SageMaker Inference: Accelerate autoscaling for your Large Language Models (LLMs) – Part 2

Flipboard

To learn more about the ModelBuilder class, refer to Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements. Lokeshwaran Ravi is a Senior Deep Learning Compiler Engineer at AWS, specializing in ML optimization, model acceleration, and AI security.

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Computer Vision and Deep Learning for Education

PyImageSearch

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. Or requires a degree in computer science? That’s not the case.

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How Qualtrics built Socrates: An AI platform powered by Amazon SageMaker and Amazon Bedrock

Flipboard

Qualtrics harnesses the power of generative AI, cutting-edge machine learning (ML), and the latest in natural language processing (NLP) to provide new purpose-built capabilities that are precision-engineered for experience management (XM). It uses managed AWS services like SageMaker and Amazon Bedrock to enable the entire ML lifecycle.

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Unlock cost savings with the new scale down to zero feature in SageMaker Inference

Flipboard

This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in the cloud. The scale down to zero feature presents new opportunities for how businesses can approach their cloud-based ML operations.

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