Issue #31: Refuel.ai. LLMs can label data better than humans. Autolabel.
Back with some news! We started a company called Refuel.ai - helping teams create clean, labeled datasets at the speed of thought.
Machine Learning Ops Roundup
Why is machine learning in the real world hard and how do you make it better? This newsletter brings together the best articles, news, and papers highlighting the challenges and opportunities in MLOps
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Read 2 days ago and current, but nothing has been published for 3 years.
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Issue #30.5: Special Announcement - A new course on MLOps!
Welcome to the latest issue of the MLOps newsletter.
Issue #30: ML Platforms. On Deck Data Science. Explainability in Healthcare. Re:Invent. ML for Content Moderation.
Happy New Year and welcome to the 30th issue of the MLOps newsletter.
Issue #29: State of AI. Kaggle ML Survey. ML Deployment at Reddit. Inferentia.
Welcome to the 29th issue of the MLOps newsletter.
Issue #28: MAD Landscape. Covid-19 Border Testing. Blocking Spam@Slack. Applying ML. Scikit-learn 1.0.
Welcome to the 28th issue of the MLOps newsletter. We really enjoyed writing this one, hope you enjoy it too! In this issue, we briefly cover Nihit’s interview with Eugene Yan, discuss Matt Turck’s ML, AI, and Data landscape, share a cool ML-based invite spam detection from Slack, and dive into a fascinating reinforcement learning system for COVID testing.
Issue #27: Medical Imaging Challenges. Machine Unlearning. Managing Supply and Demand. AI Sandbox.
Welcome to the 27th issue of the MLOps newsletter. It is officially one year since we started writing this newsletter, and we are incredibly grateful for your support. We are excited for many more years to come! 🎉 In this issue, we cover ... Thank you for subscribing. If you find this newsletter interesting, tell a few friends and support this project ❤️
Issue #26: Concept Drift. Anomaly Detection with Self-Supervision. NLP in Legal Applications. Models Per Customer?
Welcome to the 26th issue of the MLOps newsletter.
Issue #25: Tesla AI Day. Feature Stores. NIST on AI bias. Model monitoring tips. AI and COVID.
Welcome to the 25th issue of the MLOps newsletter. In this issue, we cover Tesla AI Day, a short paper about gaps in feature stores, updates about the NIST proposal to reduce bias in AI, tips on ML monitoring, and a tech review about the challenges of deploying AI tools for diagnosing COVID.
Issue #24: AI at Porsche. Efficient Inference. Bootstrapping Labels. Nearest-Neighbor Benchmarks.
Welcome to the 24th issue of the MLOps newsletter.
Issue #23: AI Regulations. Efficient Active Learning. Model Health Assurance. Vertex Matching Engine.
Welcome to the 23rd edition of the MLOps newsletter. In this issue, we cover updates on AI regulations and frameworks in the EU and the US, a recent paper on web-scale active learning, details about LinkedIn’s internal platform for model observability, and a summary of Google’s new scalable vector similarity search.