New course from Andrew Ng's DeepLearning.AI in collaboration with AWS on Generative AI 🚀 It includes data gathering, model selection, performance evaluation, deployment, and how to adapt and optimize models to various use cases. deeplearning.ai/courses/genera… #ML #AI

Stanford has put together an informative repo which introduces the "Foundation Model Transparency Index"; a framework which rates major AI providers like OpenAI and Google on their adherence to requirements specified in the EU Parliament's AI Act. Repo: github.com/stanford-crfm/…

Dealing with Train-serve Skew in Real-time ML Models: A Short Guide 🔭 A comprehensive article that demystifies the training-serving skew on ML models, which arises due to differences between training and serving environments in real-time ML models building.nubank.com.br/dealing-with-t… #ML

🚀 This week in Machine Learning at Scale 🚀 In this edition we cover: 1) ML System Design Case Studies 2) Future of Custom Tuned LLMs 3) LLM App to Prod Databaricks 4) + more 🚀 linkedin.com/pulse/issue-23… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps

ML System Design Case Studies 🖥️ Evidently AI created a fantastic resource containing 200 real-word case studies of ML Systems from 64 companies including Netflix, Airbnb, and Doordash. evidentlyai.com/ml-system-desi… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps

Future of Custom & Fine-Tuned LLMs 🔮 A great article from Outerbounds, the company behind Metaflow, which explores instruction tuning for large language models. outerbounds.com/blog/custom-ll… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps

New free online course on "Large Language Models: Application through Production" 💡 A great resource for developers, data scientists, and engineers who aim to build applications powered by large language models. edx.org/course/large-l… #ML #MachineLearning

Meta / Facebook has released their "approach to explaining (ML) ranking" 💡 This includes how posts are ranked in newsfeed, recommendations, ranking of comments, friend recommendations, notifications and more. transparency.fb.com/features/expla… #ML #MachineLearning

Fantastic episode of"Talk Python Podcast" on"Python at Netflix" featured two guests from Netflix's Python Infrastructure team, Amjith Ramanujam and Srinivasan Ramanujam 📺 youtube.com/watch?v=yPBslO… #ML #MachineLearning #ArtificialIntelligence #AI #MLOps #AIOps #DataOps

In Machine Learning, Spreadsheets just keep coming back - this time as one of the top choices for experiment tracking and model registry tools... Only a week since we launched our survey on the State of Production ML we are already seeing great insights, help us map the broader

We are pleased to announce that our next speaker is Alejandro Saucedo on November 18. Register and find out more! ieai.sot.tum.de/event/speaker-… Christoph Lütge Alejandro Saucedo | KubeCon 2025 AI Day Keynote #ieai.sot.tum.de #ai #artificialintelligence #aiethics

Insightful news, resources and frameworks in the Machine Learning Ecosystem this week: National AI Strategies & Regulation, Netflix's Large Scale Time Series Infra, Gauge on GenAI's Tech Debt Costs, Gradient Flow on AI Engineers, MLOps Organisational Setups + more 🚀 Check out

Central functions support machine learning ambitions across organisations; only ~30% of organizations have a central Data / ML platform, and less than 10% have central AI Risk Governance: Establishing central functions to support teams is a growing trend in machine learning

🥳🥳🥳 Happy New Year 2025 🥳🥳🥳 How time flies! We are celebrating 6 years since starting this weekly MLE newsletter 🎉🎉🎉 Check out the deep dives and resources in this week's edition: buff.ly/3U7DCrp

Landed in London for #KubeCon Europe! If you are around let's catch up! Also join us tomorrow in our opening keynote at the KubeCon AI Day on the state of GenAI & ML in the Cloud Native Ecosystem 🚀