Deliver high-performance ML models faster with MLOps tools

[@humanity-indian]

Great Tutorial

[@svitlanatuchyna7154]

This tutorial is a good general overview of SageMaker for those who already have quite a lot of experience in ML. But it is definitely not suitable for beginners. The first part was easy to follow but the second part was more confusing.

[@be_present_now]

@awssupport Could you please record the tutorials in higher resolutions preferebly 1080p so that code is crisply visible for a better learning experience. Thanks!

[@GenAIML_senseNsimplicity]

The github code repository does not have 00_EDA_Local.ipynb, 01_DataPrep.ipynb etc files. Where to find these files?

[@chsaloua]

Thank you guys for the tutorial.
I had a problem implementing the scripts for SageMaker experiments. It appears that when working with SageMaker experiments, it's important to separate the training script from the SageMaker-specific code for managing experiments. So the "preprocessing.py" and "train.py" should not include any SageMaker-specific commands.

[@sndrstpnv8419]

hi where is link for code pls

[@awssupport]

Hi there, I've passed along your request internally. 📨 We'll follow up if we're able to provide what you're looking for. If anything else comes up, explore our help options here: go.aws/get-help. 🔭 ^KB

[@sndrstpnv8419]

@@awssupport any updates, why to hide open source code , what already was shown on video ?

[@MrKB_SSJ2]

17:39

[@sumitvaise5452]

Good explanation regarding DS but worst MLOPS explanation