Build a custom ML model with Vertex AI

[@SandeepSingh-mw1pw]

Does vertexAI support multi model endpoints similar to AWS sagemaker.

[@raharijaonazolalainayannic7851]

Does Vertex AI allow to manage the batch prediction in an easy way?

[@tusharmalhotra6686]

When you made use of tensorflow framework to build the model, then why did you choose "custom" model in the options

[@MeronMuche]

Because she used custom training instead of AutoML. When she trained it, she used custom containers. For the endpoint, she used a prebuilt tensorflow container.

[@yudhveersingh655]

Nice explanation

[@saidbenaissa7179]

Awesome job

[@rajrajabhathor2996]

Great! But unfortunately way too many steps...

[@dec13666]

So "Custom Training" is only enabled for Tensorflow, scikit-learn and XG-Boost? Not "that custom" after all...

[@GregPriday]

Prebuilt containers only support those 3. You can use whatever you want if you create a custom container.

[@yasserfarman8231]

Wertex AI changed my life ..

[@Alice8000]

Dear Sir please do not be racism. 🙏🏼

[@agucci-e8x]

Ah. Posted 3 days ago. I'm lucky vertex AI is getting deployed and documented as I'm getting into ml.

[@akkis_m]

UI Inconsistent with reality - where is the Notebooks tab??? 👎

[@bashbash]

awesome

[@sokhuonwath2444]

Good

[@Ejnota]

esto ya se ha ido de madre

[@whitetiger1810]

this tutorial really blows... also, the container registry used in the video is now deprecated

[@samiamgreeneggaandham]

vertex ai is supposed to be a virtually automated thing. here it is talking about having to write code for prepackaged containers. 0 out of 5 stars for this video. reported for spam and misleading.

[@dislike__button]

Good luck getting a GPU quota. Spolier: you will not get it.