Hello. First of all, i'd like to thanks for such a good intro into the subject. But i would like to know if, with MLFlow Projects, its possible to get the model from a remote repo using poetry's venv and not conda's (and if yes, should we just use the same yaml file, but with different env keys)?
1:02 - Outline
2:33 - ML lifecycle
6:58 - MLflow for standardizing the ML-Lifecycle
8:35 - Key Components of MLflow
11:09 - MLflow Tracking
15:23 - MLflow Models
17:59 - MLflow Projects
19:23 - Setup and Notebooks for Code-along Session
22:18 - Question : MLflow support for Deep learning
25:15 - Question : Reproducibility with MLflow
29:18 - Code-Along Session Start
36:00 - Code-Along : Regression Example with MLflow
1:02:54 - Code-Along : Classification Example with MLflow
1:11:52 - Code-Along : Searching Runs
1:14:20 : Code-Along : Model Serving
1:21:08 - Code-Along: Reproducibility
1:23:34 - Conclusion
Thank you so much for your presentation
kalyan and karishma , u both explained it really well. lot of precise information. cleared many doubts. thanks a lot guys and PyData.
Hello. First of all, i'd like to thanks for such a good intro into the subject. But i would like to know if, with MLFlow Projects, its possible to get the model from a remote repo using poetry's venv and not conda's (and if yes, should we just use the same yaml file, but with different env keys)?
Can u pls share the code for this session. Thanks in advance
drive.google.com/drive/folders/1Hg37oOx-z81pdLc3W644P_kRaoG_W7s2
Hi, Can you please share the code used in the session. Thank you
see 20:56 - "session notebooks are available at ... "
thank you guys