MLflow Crash Course - Model Registry and Model Deployment

Рет қаралды 7,123

Күн бұрын

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: colab.research.google.com/dri...
The Mario vs. Wario project that we used for the demo - dagshub.com/nirbarazida/mario...
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: dagshub.com
📖 Our Blog: dagshub.com/blog/
🥰 We welcome you to join our community on Discord: / discord
Social Links:
🔗 LinkedIn: / dagshub
🐥 Twitter: / therealdagshub
DAGs out 🤙🏼

Пікірлер: 9

@curdyco 3 ай бұрын

where did your terminal came from? is it in your laptop? or is it in dagshub? do i pull the repo in my pc and then run the terminal?

@curdyco 3 ай бұрын

you are using dvc command why? is there any detailed tutorial for that?

@curdyco 3 ай бұрын

In the conda env why you only used mlflowm pillow and tf, is the because register_pyfunc were using them, but register_pyfunc was also using io, and base64?

@DagsHub 3 ай бұрын

io, and base64 are system packages that come with python, so you don't need to mention them

@curdyco 3 ай бұрын

@@DagsHub okay, and in conda env we add only libraries that we are using in register_pyfunc?

@curdyco 3 ай бұрын

you are building mlflow model build-docker to create container but where is the rest api code? how can i customise the interface for user?

@DagsHub 3 ай бұрын

Can you clarify what you mean? I'm not sure I understand the question

@curdyco 3 ай бұрын

@@DagsHub see you said we can build a docker container using the command i mentioned above, but that docker container will not have app.py, only the model is inside the container, what about the web interface like with flask or something? what about dockerfile?