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Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

AWS Machine Learning Blog

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

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How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker

AWS Machine Learning Blog

However, there are many clear benefits of modernizing our ML platform and moving to Amazon SageMaker Studio and Amazon SageMaker Pipelines. Model explainability Model explainability is a pivotal part of ML deployments, because it ensures transparency in predictions.

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How ChatGPT really works and will it change the field of IT and AI??—?a deep dive

Chatbots Life

As everything is explained from scratch but extensively I hope you will find it interesting whether you are NLP Expert or just want to know what all the fuss is about. We will discuss how models such as ChatGPT will affect the work of software engineers and ML engineers. and we will also explain how GPT can create jobs.

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Use IP-restricted presigned URLs to enhance security in Amazon SageMaker Ground Truth

AWS Machine Learning Blog

Use Amazon SageMaker Ground Truth to label data : This guide explains how to use SageMaker Ground Truth for data labeling tasks, including setting up workteams and workforces. Abhinay Sandeboina is a Engineering Manager at AWS Human In The Loop (HIL). Understanding how presigned URLs work will be beneficial.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. Feature Engineering. The new category is often called MLOps.

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Bria 2.3, Bria 2.2 HD, and Bria 2.3 Fast are now available in Amazon SageMaker JumpStart

AWS Machine Learning Blog

In this post, we discuss Bria’s family of models, explain the Amazon SageMaker platform, and walk through how to discover, deploy, and run inference on a Bria 2.3 HD – Optimized for high-definition, Bria 2.2 About the Authors Bar Fingerman is the Head of AI/ML Engineering at Bria. model using SageMaker JumpStart.

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Automating the Automators: Shift Change in the Robot Factory

O'Reilly Media

This mindset has followed me into my work in ML/AI. Because if companies use code to automate business rules, they use ML/AI to automate decisions. Given that, what would you say is the job of a data scientist (or ML engineer, or any other such title)? But first, let’s talk about the typical ML workflow.