7 Simple Steps to Standardizing the ML Experiment (Jan. 12)
Notes from the second session of a brand new Office Hours series: Seven Simple Steps to Standardizing the Experiment discussing how to define scope and success for an ML project.
Comet’s Year-in-Review: 2021
Notes from this week's Comet Office Hours: Revisiting the fundamentals and Harpreet's Google Search crash course
Streamline Model Development with GitLab’s DevOps Platform and Comet
Leverage GitLab’s powerful CI/CD pipelines and Comet’s Experiment Management capabilities to create a model development workflow that enables better collaboration…
Build ML Models Faster with New Relic One and Comet
If you’re a data scientist, machine learning engineer, or data engineer, you know the challenges of deploying a successful machine…
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
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
Comet Office Hours: Recap for August 29, 2021
Notes from this week's Comet Office Hours: Baseline models and experiment management, pitching the need for better data foundations, and tips for recharging
