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RecList: The better way to evaluate recommender systems
How the team behind RecList is moving ML forward When it comes to evaluating ML models, there’s debate about which…
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Putting Machine Learning Models Successfully into Production
Sharing insights from Convergence speakers in advance of the free-to-attend, one-day virtual machine learning conference
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Issue 18: Self-regulating AI Ethics, TensorFlow Similarity, 3D Dance Generation, and Textless NLP
Self-regulating AI ethics, TensorFlow Similarity, 3D dance generation, and textless NLP
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Issue 17: Graph Neural Nets, Concept Drift Deep-dive, Rethinking Large Language Models
Graph neural nets, concept drift deep-dive, rethinking large language models, and more
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Issue 16: AI Writes a Play, Hugging Face’s High-profile Hire, New Text-to-speech Model from Google
An upcoming MLOps webinar, Hugging Face’s latest high-profile hire, an excellent extractive text summarization project, and a new neural TTS…
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Issue 15: Tesla’s ‘AI Day,’ AI Story Generation, Model Monitoring Tips
Tesla doubles down on becoming an AI leader, ML research’s struggles with reproducibility, a deep dive into automated story generation,…
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Issue 14: Nvidia’s Computer-generated CEO, Snap’s Use of GPUs for Model Inference
Nvidia shows off its AI+computer animation capabilities, Snap invests in GPU-accelerated inference, and estimating the weight of an object with…
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Issue 13: ML for Creative User Interfaces and Experiences, Samples from Our AI Art Gallery
A new Comet Industry Q&A, a sampling of user submissions to our CLIPDraw public AI art gallery, and a few…
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How to Tackle 3 Common Machine Learning Challenges
Here are 3 common machine learning challenges and how to tackle them: 1. Building a good enough model: From our…
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Issue 11: Announcing Comet Artifacts, the Case for Automating Morals
A new Mozilla study on the “horrorshow” of YouTube’s recommender system, notes from a Turing Lecture given by three deep…
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