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

AWS Machine Learning Blog

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services.

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Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements

Flipboard

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. For example: input = "How is the demo going?" Models are packaged into containers for robust and scalable deployments.

ML 167
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ML Days in Tashkent — Day 3: Demos and Workshops

PyImageSearch

But again, stick around for a surprise demo at the end. ? This format made for a fast-paced and diverse showcase of ideas and applications in AI and ML. In just 3 minutes, each participant managed to highlight the core of their work, offering insights into the innovative ways in which AI and ML are being applied across various fields.

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Qwen 2.5 Coder 32B: Is This Best Open Weight Model Better than GPT-4o and Claude 3.5 Sonnet

Towards AI

coder:32b The latest series of Code-Specific Qwen models, with significant improvements in code generation, code reasoning, and… ollama.com You can also try out the model on the demo page of Hugging Face: Qwen2.5 Coder Demo – a Hugging Face Space by Qwen Discover amazing ML apps made by the community huggingface.co

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Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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Eventual (YC W22) Is Hiring a Developer Relations Manager for Daft (SF)

Hacker News

ABOUT EVENTUAL Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI. Eventual and Daft bridge that gap, making ML/AI workloads easy to run alongside traditional tabular workloads. This is more compute than Frontier, the world's largest supercomputer!

ML 130
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Enterprise-grade natural language to SQL generation using LLMs: Balancing accuracy, latency, and scale

Flipboard

The API is linked to an AWS Lambda function, which implements and orchestrates the processing steps described earlier using a programming language of the users choice (such as Python) in a serverless manner. The demo code is available in the GitHub repository. Thomas Matthew is an AL/ML Engineer at Cisco.

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