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The Rise and Fall of Data Science Trends: A 2018–2024 Conference Perspective

ODSC - Open Data Science

AI engineering extended this by integrating AI systems more deeply into software engineering pipelines, making it a crucial field as AI applications became more sophisticated and embedded in real-world systems. Takeaway: The industrys focus has shifted from building models to making them robust, scalable, and maintainable.

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Why Software Engineers Should Be Embracing AI: A Guide to Staying Ahead

ODSC - Open Data Science

The rapid evolution of AI is transforming nearly every industry/domain, and software engineering is no exception. But how so with software engineering you may ask? These technologies are helping engineers accelerate development, improve software quality, and streamline processes, just to name a few.

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Improving air quality with generative AI

AWS Machine Learning Blog

LLMs excel at writing code and reasoning over text, but tend to not perform as well when interacting directly with time-series data. With AWS Glue custom connectors, it’s effortless to transfer data between Amazon S3 and other applications.

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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning Blog

About the authors Samantha Stuart is a Data Scientist with AWS Professional Services, and has delivered for customers across generative AI, MLOps, and ETL engagements. He has touched on most aspects of these projects, from infrastructure and DevOps to software development and AI/ML.

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Learnings From Building the ML Platform at Stitch Fix

The MLOps Blog

This is Piotr Niedźwiedź and Aurimas Griciūnas from neptune.ai , and you’re listening to ML Platform Podcast. Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. As you’ve been running the ML data platform team, how do you do that?

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