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Comet provides a self-hosted and cloud-based MLOps solution that enables data scientists and teams to track, compare, explain and optimize experiments and models.

We all know that machine learning is iterative, complex, and — at times — messy. Managing your experiments and automating the most tedious parts of the ML process are often the best place to start when it comes simplifying and making your job easier. This session will explore how experiment management can help you:

  • Automatically track datasets, code changes, experimentation history and production models creating efficiency, transparency, and reproducibility – all at scale
  • Standardize and track experiments across data science teams, even in large organizations
  • Deliver custom visualizations and reports, to clearly communicate the results of your research


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