From Training to Production: How to Fit Neptune in Your Machine Learning Model Lifecycle?

1 min
Parth Tiwary
21st April, 2022

What will you learn?

In this webinar our experts share what they’ve learned when talking to hundreds of teams looking for the solution to organize the model development lifecycle and track metadata from each stage of the process.

The agenda:

  • A high-level overview of MLOps landscape
  • What is the ML model lifecycle?
  • Major challenges/complexities in ML model lifecycle
  • How you can use Neptune for:rn
    • Experiment tracking
    • Model fine-tuning
    • Logging metadata from monitoring and production environment
    • Setting up automatic retaining of models using monitoring metadata
  • Tips and tricks on using Neptune in your MLOps lifecycle
  • Q&A session

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