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Workflows and processes are a critical need for every machine learning and AI project. When done well, they can enable you to operate more efficiently and ensur...
In the last three years since Comet was founded, our users and customers trained millions of models on anything from self-driving cars to speech recognition, and from Covid-19 protein prediction ...
This week's reads from the Comet team features language models, trustworthy AI, and cognition work on interacting with technical articles. Each week we'll feature a couple of awesome reads from the great minds in our c...
Comet wants to know what you're reading! There are so many articles, papers, and blog posts on Machine Learning that it's hard to keep up. One of the ways Comet wants to help you stay up to date with new devel...
In this post, we will showcase a Custom Panel dedicated to debugging object detection models. We will use the Penn-Fudan Pedestrian Detection dataset, along with a Faster-RCNN model, with a Resnet5...
Machine Learning models tend to perform inconsistently across different parts of a dataset. Summary performance metrics such as AUC, and F1, are not enough to identify the parts of the data where a model need...
Hugging Face provides awesome APIs for Natural Language Modeling. In particular, they make working with large transformer models incredibly easy. These models can be used off-the-shelf for text generation, translation, an...
Comet recently hosted the online panel, “How do top AI researchers from Google, Stanford and Hugging Face approach new M...
Comet recently hosted the online panel, “How do top AI researchers from Google, Stanford and Hugging Face approach new ML problems?” This is the second post in a series where we recap the q...
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