MLflow Crash Course - What is MLflow & MLflow Tracking
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, Shambhavi covers the following topics: 1) Intro to MLflow - Learn what MLflow is and how it can help you manage your machine learning project. 2) Experiment Tracking - live logging of parameters, metrics, and artifacts as part of machine learning experiments. 3) Hands-on experience using MLflow Tracking! 📚 Additional Materials: The Colab Notebook with the theoretical information about MLflow and MLflow Tracking demo - https://colab.research.google.com/dri... The Mario vs. Wario project that we used for the demo - https://dagshub.com/nirbarazida/mario... Time-stamps 00:00 - Meet & Great 03:13 - Intro + Signup 07:08 - Agenda 07:54 - Why do we need MLflow 10:52 - What is MLflow 15:40 - MLflow Tracking Functionality 19:30 - How and where runs are recorded? 25:30 - Hands-on experience using MLflow Tracking! 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: / discord Social Links: 🔗 LinkedIn: / dagshub 🐥 Twitter: / therealdagshub DAGs out 🤙🏼
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01. Introduction To MLflow | Track Your Machine Learning Experiments | MLOps
