Wow... I loved this presentation... so useful🤩 Thank you so much
@andreiladyka328729 күн бұрын
Ngrok is not secure!!!
@KardinoIas3 ай бұрын
Sveiki 🙂
@faiyazhasan47974 ай бұрын
Anyone get any warning saying could not modify ulimit?
@chineduezeofor24814 ай бұрын
Excellent tutorial!
@ravindarmadishetty7365 ай бұрын
Do you have a continuation video for it?
@wizardaka6 ай бұрын
My dear this is a brilliant intro to Shiny in terms of concepts, has opened my eyes and massively improved my understanding
@fabsync6 ай бұрын
fantastic video! Love your teaching style! It will be great to see a video on how to set ray on docker for local development.. probably chat with your pdf tutorial?
@valour.se477 ай бұрын
why did you miss the IAM roles and Permissions part ?
@philipchuks24277 ай бұрын
Well, your video just saved my day!!! Thank you
@fkeb37e9w07 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.
@caty8637 ай бұрын
I wanted to see how you added that logo and top banner text and photos. I felt cheated to watch all the video and not see what I came for.
@user-dx3uu1ed6f6 ай бұрын
Likewise. Hoped for a repo in the description but alas. It's still an awesome vid tho.
@yaseenbaba33898 ай бұрын
Excellent
@ccqf46949 ай бұрын
Great video ❤❤❤ thanks
@rodolphobabatounde67119 ай бұрын
It's really sad that I didn't share the code or the link to your blog. We need at least the yaml file
@benjaminosawe1819 ай бұрын
how you used the ip address and script to bring up Jupyter was not made clear, not very helpful video
@Anton_Sh.10 ай бұрын
But how do you get one ? :)
@arguscesus10 ай бұрын
We’re you able to run tensorboard for ray machine learning task?
@PompiBasumatary-s4g10 ай бұрын
Takes a lot of time for the cluster to be set up .
@saif3r10 ай бұрын
Great video, thank you very much!
@srikanthdongala692210 ай бұрын
Good Job!
@electricweegie912510 ай бұрын
Excellent demo! Would be great to share the code.
@josephmiano200611 ай бұрын
Great video, thanks. I did have one question; is there a way to also version control the data that the model was trained on? It is super useful to be able to track several versions of the model in production, but in my usecase I also may want to also track the dataframe that each version of the production model was trained on. Can MLFlow do this or do you know any other tools that can easily integrate with MLFlow for this?
@marioseguraiglesias60384 ай бұрын
DVC is for data version control
@user-kp2mi4ky7c Жыл бұрын
it helped me a lot
@zahabkhan6832 Жыл бұрын
where is the blog post
@Pooh991 Жыл бұрын
Thaks for the video! It worked for the most part and then I had an error: ParamValidationError Traceback (most recent call last) - any thoughts would be appreciated! thank you!
@sidmehta1905 Жыл бұрын
So good. Your enthusiasm & relatable communication made this easy to understand. Thanks for putting this out there!
@brittnyfreeman59089 ай бұрын
Couldn't have said it better myself. Your passion for this subject matter is contagious.
@guilhermeuchoa1147 Жыл бұрын
How did you set the password? Very helpful video, thanks!
@javiergutierrez29588 ай бұрын
If you still need it, there is a default password for jupyter hub is : jupyter
@reneporto-ai Жыл бұрын
Very helpfull bud, thanks a lot.
@LeoUfimtsev Жыл бұрын
I can't use Ngrok for company security policies. Was looking for a native solution.
Жыл бұрын
Maravilhoso! Estava procurando alguma coisa parecida! E se meu bucket tiver milhares de pastas e arquivos? Como pego somente uma pasta para fazer análise no sagemaker?
@shathishwarmas1243 Жыл бұрын
I had Issue on Waiting for oidc-authservice pods to be ready ... running command: kubectl wait --for=condition=ready pod -l 'app in (authservice)' --timeout=240s -n istio-system error: timed out waiting for the condition on pods/authservice-0 Waiting for oidc-authservice pods to be ready ... running command: kubectl wait --for=condition=ready pod -l 'app in (authservice)' --timeout=240s -n istio-system error: timed out waiting for the condition on pods/authservice-0 Waiting for oidc-authservice pods to be ready ... running command: kubectl wait --for=condition=ready pod -l 'app in (authservice)' --timeout=240s -n istio-system error: timed out waiting for the condition on pods/authservice-0 is there any additional volumes to be attached ?
@prashanthb6521 Жыл бұрын
Flew over my head :(
@Tbone913 Жыл бұрын
Excellent, thanks
@abhishektrivedi7291 Жыл бұрын
Video was good, why do not you share the yaml file or the blogpost to get them
@karenschmalbach5985 Жыл бұрын
Your vid has been really helpful to me, thanks
@kc_ayem4961 Жыл бұрын
thanks so much !!! it is so clear. I have a question though how much does the bucket, with cognito service and the the UI hosting costs you per month or week? And is there any options to reduce the costs in any manners ?
@franciscocreatorstargazer6165 Жыл бұрын
Hi can you make a tutorial on how to deployu to prod already trained models?
@zcliu-uy1ze Жыл бұрын
不错不错
@killerthoughts6150 Жыл бұрын
Thanks for the video, looking forward to more!
@deidy2005 Жыл бұрын
Do you hava something related to inference?
@badraboufirasse433 Жыл бұрын
Very helpful. Thanks
@javierturcotte Жыл бұрын
😎 "PromoSM"
@daycentmodel9086 Жыл бұрын
Thanks for a very intuitive demo! Where do I find the blog posts that you mentioned?
@user-jx3op2nn2f Жыл бұрын
hey, could you please give some explanation for the dockerfile. thanks.
@esthermatara9005 Жыл бұрын
Thank you
@gatorpika Жыл бұрын
Very cool talk and demo, thanks!
@user-bt6pp1dt4w Жыл бұрын
You could have just said Databricks is not great.
@owlprotravels Жыл бұрын
Saturno Cloud, by chance I found you on google. I liked more than what they present on the site. I'm a student, I wanted to be able to train and test models. That I created in college for my studies. I wanted to know if to create my account on your platform, I will need a credit card like in aws or google cloud. I'm in this doubt and I still haven't created an account for this question.