Learn from the DagsHub professionals what MLflow is and why it should be part of your MLOps tool kit. Gain hands-on experience using it to track experiments, register models, and deploy them to AWS.
In this session, Yono covers the following topics:
1. Model Registry - How to log and manage your machine learning models with MLflow.
2. Model Deployment - How to deploy your machine learning model to a cloud provider.
3. Hands-on experience deploying your trained model from the MLflow registry to AWS.
📚 Additional Materials:
The Colab Notebook: https://colab.research.google.com/drive/1lLO8CmqJ2wLY5nTHNMvvMYwHEJQtqQNo?usp=sharing
The Mario vs. Wario project that we used for the demo - https://dagshub.com/nirbarazida/mario_vs_wario/src/mlflow-102
Time-stamps
00:00 - Meet & Great
02:23 - Intro + Signup
05:57 - Recap of MLflow 101 Webinar
07:53 - Agenda
09:09 - Model Registry
15:50 - Model Deployment
19:10 - Hands-on experience - setup
27:03 - Hands-on experience - Model Registry
50:38 - Hands-on experience - Model Deployment
If you want to hear more about what we are doing at DagsHub, here are some interesting links for you:
🌐 Our Website: https://dagshub.com
📖 Our Blog: https://dagshub.com/blog/
🥰 We welcome you to join our community on Discord: https://discord.gg/skXZZjJd2w
Social Links:
🔗 LinkedIn: https://www.linkedin.com/company/dagshub
🐥 Twitter: https://twitter.com/TheRealDAGsHub
DAGs out 🤙🏼