MLFlow Tutorial Part 1: Experiment Tracking

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MLFlow Tutorial Part 1: Experiment Tracking

Рет қаралды 20,112

Күн бұрын

This tutorial will show you the basics of experiment tracking with MLFlow for TensorFlow, Sklearn, and other frameworks. Learn how to structurise your experiments, log everything you want, and save the best models for later use. You can code along or simply pull the notebook and read it at your own pace.
Links:
Github repo - github.com/aru...
FT Transformer Blog - / improving-tabtransform...

Пікірлер: 25

@peegee101 Жыл бұрын

Love the haircut! Nicely done!

@atruberts Жыл бұрын

Thank you so much 😀

@hndr91 8 ай бұрын

What a clear explanation, thanks man!

@atruberts 8 ай бұрын

Glad it helped!

@brahyamalmonteruiz9984 6 ай бұрын

excellent video, but the audio was too low

@AbdolaMike Жыл бұрын

Loved the video. you got my sub!

@atruberts Жыл бұрын

Awesome, thank you! Sorry for taking so long to reply, I'm planning to be more active now 🤞

@trangmun2851 8 ай бұрын

Amazing thankyou so much!

@user-pp1kg5ts7q 11 ай бұрын

Great content man ..why am i not able to see the compare button in the ui ..using 2.7.1 version in windows chrome

@fkeb37e9w0 7 ай бұрын

I am running mlflow server with local host inside a vm and using the same as tracking uri, but when I do start_run() I get an error of 400 or 403. How do I resolve this.

@NewDataTime 8 ай бұрын

Thank you

@atruberts 8 ай бұрын

You're welcome, glad you enjoyed it!

@user-fb9zv9cf1s 11 ай бұрын

Good stuff!

@miguelovallevillamil4953 Жыл бұрын

Amazing content

@atruberts Жыл бұрын

Thank you so much! More is coming soon :)

@DoubleJMc Жыл бұрын

nice!

@atruberts Жыл бұрын

Thanks buddy! I hope it's useful 😉

@Jerry-uc1pn 10 ай бұрын

Your audio is way way too soft. I could not hear anything.

@AvijeetPandey Жыл бұрын

Hi Antons, thanks for the helpful video. However, we only have access to R/Jupyter notebook inside a virtual environment at my workplace. Hence, all the ports are blocked. So, spawning that cool UI/backend server is not an option. Can we still use Mlflow tracking with just jupyter notebooks and local filesystem(maybe txt files)? Would be cool if you make a part 2 for the same.. Thanks

@atruberts Жыл бұрын

Hi Avijeet, I'm glad you liked it! Hmm, in theory everything that your experiments generate are stored locally, either in mlruns folder, or in the .db you've specified. You'll need to find out where exactly the parameters/metrics you need are stored, but once you have their location it'll be quite easy to access them and compare between each other.

@atruberts Жыл бұрын

Just out of curiosity, what does it tell you when you try to run mlflow ui command?

@AvijeetPandey Жыл бұрын

@@atruberts no issues when running the ui command, it gives me a URL with some port address, but unable to open that URL in browser due to IT policies, just like standard Web address block notice

@AvijeetPandey Жыл бұрын

@@atruberts OK, so SQLite backend is not necessary

@user-lf8yv3ls7j Жыл бұрын

I guess you can use ngrok to access your local port externally. For example, it works in Google colab to open mlflow ui. Although it seems less secure than using ui locally. You can find examples of using ngrok in zenml notebooks.